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Be a part of our success story. Launch offers talented and motivated people the opportunity to do the best work of their lives in a dynamic and growing company. Through competitive salaries, outstanding benefits, internal advancement opportunities, and recognized community involvement, you will have the chance to create a career you can be proud of. Your new trajectory starts here at Launch!

The Role:

Launch is actively seeking a visionary Solutions Architect / Principal Software Engineering Lead (AI) to design and deliver modern engineering and applied AI solutions across client engagements. This role blends deep hands‑on engineering, architectural leadership, AI system design, and client advisory. You will operate across system design, production‑grade engineering, multi‑agent architectures, cloud platform strategy, and the development of Launch’s AI practice.

Responsibilities Include:

Architecture & Technical Strategy

• Define the technical direction for client engagements end-to-end: discovery, design, build, and production hardening.
• Assess client technology ecosystems and identify high-impact opportunities for AI/ML integration.
• Lead architecture reviews, design sessions, and technology selection across cross-functional stakeholder groups.
• Translate ambiguous business problems into concrete engineering plans with clear scope, milestones, and risk callouts.

AI Engineering & Delivery

• Architect production agentic systems including multi-agent orchestration, agent harnesses, skill/tool composition, human-in-the-loop checkpoints, and inter-agent communication protocols (e.g., A2A, MCP).
• Build and govern MCP server ecosystems: design, deploy, and secure Model Context Protocol integrations connecting AI agents to enterprise data sources, internal APIs, and third-party platforms.
• Define agent skill and capability frameworks including reusable skill libraries, prompt engineering standards, and evaluation harnesses for consistent agent behavior across engagements.
• Architect RAG pipelines, fine-tuning workflows, and model lifecycle infrastructure (training, serving, experiment tracking) as foundational components of agentic systems.
• Integrate AI platforms and APIs (Azure OpenAI, Amazon Bedrock, Anthropic, Vertex AI) into production systems with enterprise-grade reliability, cost governance, and observability.
• Establish AI-native development practices: embed tools such as Claude Code, Cursor, and GitHub Copilot into team workflows with standards for AI-assisted code review, test generation, and documentation.
• Design evaluation and observability infrastructure including LLM eval frameworks, red-teaming, behavioral drift detection, and production monitoring across tool call chains, latency, and failure modes.
• Apply responsible AI governance: define guardrails, access controls, and audit patterns for agentic workflows in enterprise environments including scope containment and escalation paths.

Hands-On Engineering

• Write production code and lead by example — this role requires someone who is still close to the code.
• Design cloud-native architectures across multiple hyperscalers (AWS and Azure primarily) microservices, event-driven systems, serverless, and containerized workloads.
• Define and implement infrastructure-as-code using tools such as Terraform, Pulumi, CloudFormation, or Bicep.
• Design and optimize CI/CD pipelines, GitOps workflows, and container orchestration using Docker and Kubernetes.
• Establish observability and reliability practices using tools such as Datadog, Prometheus, Grafana, CloudWatch, or Azure Monitor.
• Drive security-by-design across the delivery lifecycle including IAM, network architecture, secrets management, and compliance automation.

Leadership & Client Advisory

• Lead engineering teams ranging from small squads to 10+ person delivery teams, scaling leadership approach to the needs of each engagement.
• Mentor and develop engineers at all levels through code reviews, pairing, and design coaching.
• Operate as a trusted advisor to client technical leadership and executive stakeholders. Communicate trade-offs clearly and build confidence.
• Influence without direct authority — driving alignment across cross-functional teams through technical credibility and stakeholder management.
• Lead discovery and requirements elicitation, surfacing the underlying business need beyond the stated request.
• Produce clear written artifacts: technical proposals, architecture decision records, SOWs, and executive-level status communication.
• Grow client relationships and identify follow-on opportunities through proposal contributions and delivery-driven account expansion.
• Contribute to Launch's growth — practice development, thought leadership, and hiring.

Qualifications:

Must-Haves:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 10+ years in software engineering with demonstrated experience in architecture and technical leadership roles.
• 3+ years hands-on with AI/ML in production. Broad fluency across generative AI (LLMs, RAG, fine-tuning, agents), MLOps (model serving, pipelines, experiment tracking), and AI-integrated product development.
• Consulting or client-facing delivery experience with a proven ability to integrate into client organizations and establish credibility with technical and executive stakeholders.
• Full-stack engineering capability across frontend, backend, infrastructure, and data layers. Proficiency in multiple modern languages (e.g., Python, TypeScript/Node.js, C#/.NET, Java, or Go) with the ability to move between them as engagements require.
• Multi-hyperscaler depth across AWS and Azure, including their respective AI/ML service ecosystems (Bedrock, SageMaker, Azure OpenAI, Azure ML). GCP experience is a plus.
• Strong fundamentals in distributed systems, event-driven architecture, API design, and DevOps/platform engineering.
• Experience leading engineering teams in agile delivery environments.
• Business acumen with the ability to connect architecture decisions to cost, timeline, and organizational impact.
• Executive presence and communication skills effective with both technical and non-technical audiences.
• Proven ability to operate in ambiguous environments and adapt to diverse client cultures.

Strong Differentiators

• Experience contributing to the development of AI engineering practices, reusable frameworks, or internal accelerators within a consulting or enterprise environment.
• Experience advising C-suite or VP-level stakeholders on AI strategy, investment prioritization, and organizational readiness.
• Depth with agentic AI frameworks (LangChain, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, CrewAI) and emerging standards like MCP (Model Context Protocol).
• Experience with enterprise data platforms (Databricks, Snowflake, BigQuery) in the context of AI/ML workloads.
• Cloud architecture certifications across AWS and Azure (AWS SA Professional, Azure Solutions Architect Expert).
• Published writing, open-source contributions, or conference speaking that demonstrates thought leadership in AI or software architecture.
• Domain depth in industries such as healthcare, financial services, retail, or public sector.

Compensation & Benefits:

As an employee at Launch, you will grow your skills and experience through a variety of exciting project work (across industries and technologies) with some of the top companies in the world! Our employees receive full benefits—medical, dental, vision, short-term disability, long-term disability, life insurance, and matched 401k. We also have an uncapped, take-what-you-need PTO policy. The anticipated base wage range for this role is $190,000 to $230,000. Education and experience will be highly considered, and we are happy to discuss your wage expectations in more detail throughout our internal interview process.

Title: Lead Software Engineer - AI Application Platform

Mode of interview 1 round in person

Location: Must be in Charlotte, NC to work Hybrid Model

Main Skill set: Python, AI and Angular

Description:

Lead Software Engineer - AI Application Platform

The Opportunity

We are seeking a Lead Software Engineer to guide the architectural development and execution of the client, a sophisticated AI-powered application generation platform. This role suits a proven technical leader with deep, hands-on expertise across the full software stack who finds enabling a team to build better software deeply satisfying.

You will shape critical systems, mentor senior and junior developers through complex technical decisions, conduct rigorous code reviews across multiple technology domains, and directly influence the platform's trajectory through strategic engineering leadership.

This is for someone who:

• Engages thoughtfully when a junior developer asks targeted architectural questions—because you see an opportunity to shape how someone thinks about systems
• Takes time to explain subtle type-safety issues in code review, understanding that feedback is a teaching moment
• Can present architecture clearly to executives and confidently explain both what we're building and why it matters
• Finds more energy in the code your team ships than in the code you write individually
• Has proven depth across the full stack and a track record of developing engineers into stronger contributors

This is not a single-language codebase. The role requires the ability to make informed decisions on TypeScript design patterns, Python FastAPI architecture, AWS security posture, and Terraform state management in context with one another.

The Platform Challenge

The client is fundamentally a Platform-as-a-Service (PaaS) for dynamic application generation. This differs from building a traditional SaaS product. Rather than building one application, you're building infrastructure that enables users to build their own applications.

What this means architecturally:

• Dynamic Content Generation at Scale: Unlike traditional development where code is fixed, AppGen generates JSON form schemas, validation rules, and UI layouts on demand. The FormBuilder component doesn't know what fields will exist until runtime. The layout engine renders user-designed screens from configuration, not hardcoded templates.
• Multi-Tenant Isolation & Data Segregation: Each user gets their own generated app, potentially deployed to their own AWS environment. The architecture must account for data isolation, namespace management, and cross-tenant security considerations.
• User-Defined Data Structures: Traditional applications are built with predetermined database schemas. AppGen works differently—form structures, field types, and validation rules emerge from user conversations with Claude. This brings engineering challenges: How do you safely execute validation logic that users define? When users modify existing forms that have thousands of submissions, how do you maintain backward compatibility? How do you version schemas?
• Content Rendering, Not Code Generation: Unlike traditional no-code platforms where users drag-and-drop to build, AppGen uses AI instead. Users chat with Claude, Claude generates a form schema, and your platform renders that schema reliably across diverse field types, validation patterns, and workflows. The system renders configurations for immediate use, rather than generating code for later deployment.

Experience that directly transfers:

• You've contributed to or led development of low-code/no-code platforms (visual builders, workflow engines, configuration-driven systems)
• You've worked on SaaS platforms with multi-tenant architecture and understand isolation strategies, rate limiting, and per-customer customization
• You've built dynamic rendering systems that handle unknown/arbitrary schemas at runtime
• You've addressed the unique challenges of treating data configurations as user-created content (form builders, report designers, automation workflows)
• You understand the difference between platform infrastructure and applications built on that infrastructure—and the architectural implications of each

Core Responsibilities

1. Technical Architecture & Systems Thinking (40%)

• Shape architectural decisions across the full stack: How should the component layer handle dynamically generated forms? What's the right approach to validate complex cross-field dependencies in the FormBuilder? What separation of concerns makes sense between the Generator Lambda and the Parent Backend?
• Guide architecture discussions: Help senior developers think through design trade-offs. Should we use NgRx or Angular signals for this feature? When does a new Lambda function become worthwhile given cold-start costs?
• Identify and address system-wide bottlenecks: Work across layers to improve performance. Explore Lambda cold-start optimization, RDS query efficiency, and DynamoDB access patterns.
• Establish patterns and guide consistency: Define coding conventions that work across Python, TypeScript, and Terraform. Help new team members understand the reasoning behind architectural choices.
• What this looks like in practice: You're able to justify architectural decisions with technical reasoning. When someone questions an approach, you can explain the trade-offs you considered. You can write code in multiple languages to validate an approach if needed.

2. Code Review & Technical Guidance (30%)

• Full-stack PR reviews: Review Python FastAPI endpoints and Angular components with equal depth, understanding how they interact.
• Deep technical review: Catch issues thoughtful code review can surface:
• RxJS Observable lifecycle and potential memory patterns in Angular
• Query efficiency and data loading patterns in SQLAlchemy
• Terraform module organization and state management implications
• Type safety and TypeScript coverage gaps
• AWS security and IAM configurations
• Educational feedback: Your code reviews help the team learn. When you identify an issue, reviewees understand not just what changed, but how to think about similar problems in the future.
• Define quality expectations: Work with the team to establish what \"production-ready\" means for this platform and support consistent application of those standards.
• What this requires: Experience reviewing code across teams and multiple languages. You know how to write feedback that resonates—clear, constructive, and focused on helping people improve.

3. Mentorship & Team Development (20%)

• Expand specialist capabilities: Help backend specialists learn to contribute to the forms-engine. Support frontend experts in understanding FastAPI patterns.
• Accelerate junior developers: Pair on complex problems. Explain the reasoning behind patterns like DataState. Connect architectural choices to implementation details and performance implications.
• Identify and address gaps: Recognize when someone is struggling with a technology and provide targeted support—training, pair programming, or guidance through architectural decisions.
• Create growth opportunities: Stretch the team into new areas. A backend engineer working on their first Terraform contribution. A frontend specialist implementing an AWS Lambda authorizer.
• What this requires: Genuine investment in people's growth. You've walked developers through major transitions (generalist to specialist, specialist to full-stack, or into new technology areas). You understand that team strength grows when individuals expand their capabilities.

4. Stakeholder Communication & Technical Leadership (10%)

• Explain to diverse audiences: Translate architectural choices and trade-offs for product managers, executives, and business stakeholders. Connect \"optimizing DynamoDB queries\" to \"improving form submission latency by 30%.\"
• Shape technical direction: Contribute the engineering perspective on feasibility, risk, and what unlocks future capabilities.
• Support release confidence: You understand the code changes, comprehend the risks, and know what to monitor. You can stand behind releases.

Required Qualifications

Technical Skills

Frontend (Production Experience)

• 5+ years of Angular (including handling version migrations, optimizing change detection, and guiding teams through reactive patterns)
• Strong TypeScript skills with generics, discriminated unions, and strict mode
• RxJS depth: You understand hot vs. cold observables, unsubscription patterns, and can identify potential memory issues in reviews
• NgRx state management: You've designed stores at scale, optimized selectors, and evaluated architectural implications
• CSS Grid & Responsive Design: You can assess component hierarchy and layout decisions
• Material Design: You've worked within it and know when and how to extend it

Backend (Production Experience)

• 5+ years of Python (async/await, type hints, data modeling)
• FastAPI production experience: session management, dependency injection, middleware
• SQL and ORMs (SQLAlchemy): You write efficient queries and review them critically
• AWS services: Understanding of Lambda behavior, IAM least-privilege patterns, VPC networking
• REST API design: Versioning, error handling, idempotency
• Testing frameworks: pytest, testing st

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• A typical day will involve a mix of hands-on coding, architectural design, and research.
  
• The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
  
• This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
  
• They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
  

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• Python
  
• JavaScript/TypeScript
  
• AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
  
• AI Models (e.g. Claude, OpenAI, etc.)
  
• AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
  
• Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
  
• Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
  
• API Design
  

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• Deep hands-on experience in Python for AI/ML development.
  

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• Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
  
• Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
  
• Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
  

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• Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
  
• Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
  
• Experience developing autonomous agents using cloud-based AI services.
  
• Experience with prompt engineering techniques and model fine-tuning.
  
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
  
• Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
  

Apply here: (s) Ruru Hoong, Anya Shchetkina, and Jimin Nam (MIT Sloan) are seeking motivated and detail-oriented individuals to work as full-time pre-doctoral researchers. The position involves close collaboration with 1-2 faculty members (depending on research interests) on empirical research projects related to digital technologies, advertising, and AI. You will contribute at all stages of the research process — from data collection and cleaning to analysis and writing. Some structural modelling or applied ML methods development may be involved if of interest.

Active and planned research projects include: 

• The design of information for human-AI collaboration
• The impact of generative AI on worker productivity, task allocation, and organizational design
• The design of AI-driven hiring tools, such as optimizing voice-AI interviews for candidate screening
• Youth, social media, and smartphones
• The effects of AI on education and learning, including adaptive AI tutoring and path dependence in AI product rollout
• AI and wellbeing, including how generative AI tools affect individual and worker wellbeing
• Household and business surveys on electricity in Ghana
• Mechanization and preferences - marketing in 19th Century tea
• Measuring advertising effectiveness with aggregate data
• Experimental design under privacy constraints
• Identifying limits of targeting and personalization effectiveness 

Methods used across these projects include randomized controlled trials, experiments, machine learning, natural language processing, large language models, probabilistic ML, and adaptive learning (bandits and Bayesian optimization).

A core goal of the position is to prepare you to apply to and succeed in PhD programs in marketing, economics, management, operations or related fields. We will work together to develop your research skills — beginning with careful research workflow and attention to detail, and progressing toward more independent analysis over time. We will also collaborate on other elements of your preparation, including independent research, letters of recommendation, and coursework planning. You will be encouraged to attend seminars and engage with the broader research community at MIT Sloan and across MIT.

You do not need to arrive with a polished skill set; the purpose of a predoc is to also help you develop that training. What matters most is a genuine interest in these research questions, a willingness to learn, and the determination to see difficult problems through. 

Principal responsibilities

• Collect, clean, and manage large-scale quantitative and qualitative datasets across active research projects related to marketing, digital economics, and AI
• Conduct empirical analysis using methods such as causal inference, machine learning, NLP, and experimental design
• Contribute to all stages of the research process — from literature review and data collection through analysis and writing
• Design and implement surveys and experiments using tools such as Qualtrics and oTree
• Write, review, and maintain reproducible research code in Python, R, or Stata, including responsible use of AI coding tools
• Other duties as needed

Qualifications

• A Bachelor's degree with strong grades, ideally in a quantitative field
• Comfort with or eagerness to learn programming (Python, R, or Stata) and experimental tools (Qualtrics, oTree)
• Willingness to experiment with AI coding tools (e.g., Claude, Cursor, Copilot) while maintaining a healthy skepticism — you should be prepared to understand and review every line of code these tools generate
• A long-term interest in pursuing a PhD in marketing, economics, management, operations, or a related field.
• A familiarity with causal inference or Bayesian statistics is welcome but not required
• Prior research experience is a plus but not a prerequisite
• Careful attention to detail — the kind of person who double-checks a merge and notices when a number doesn't look right
• Curiosity, initiative, and the persistence to work through open-ended problems
• The ability to work independently
• Visa sponsoring will not be available for this position. Candidates should have authorization to work in the US for the duration of the appointment. 

The position is located at the MIT Sloan School of Management in Cambridge, Massachusetts. The default start date is July 1, 2026, with some flexibility to begin earlier or later. The position typically lasts 1-2 years prior to entering a PhD program. Salary is competitive with other pre-doctoral research positions (50-63k). Applications will be reviewed on a rolling basis.

Application Instructions

If you are interested, please submit the following:

• A one-page cover letter describing your background, research interests, coding experience, and future goals. Please indicate which of the research areas listed above interest you most and why.
• A CV
• A transcript
• A writing sample — a research paper, term paper, or thesis that reflects your analytical abilities
• (optional) A code sample you have written, with a brief summary of what it does and the outputs it produces
• The names and contact information of two references
• Applications will be reviewed on a rolling basis starting early March until the position(s) are filled.

** To comply with regulations by the American with Disabilities Act (ADA), the principal duties in position descriptions must be essential to the job. To identify essential functions, focus on the purpose and the result of the duties rather than the manner in which they are performed. The following definition applies: a job function is essential if removal of that function would fundamentally change the job.

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• Provide deep technical leadership to a portfolio of high impact data science initiatives involving sales and advisor experience. Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery. Remove complex technical impediments
  
• Leverage your experience and skills to identify new opportunities where data science and AI can improve experiences, gain efficiencies, and generate sales.
  
• Manage team members in AI/ML and model development, testing, training, and tuning. Apply hands-on experience to ensuring best-in-class model development. Mentor team members in technical skill development and product ownership.
  
• Communicate clearly and concisely, in writing and verbally, all facets of model design and development. Continuously look for insights in models developed and generate new ideas for model improvement.
  
• Manage external vendors in the execution of parts of the data science development process as needed.
  
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code on Prudential's AI/ML platform.
  
• Bring a deep understanding of relevant and emerging technologies, give technical direction to team members and embed learning and innovation in the day-to-day.
  
• Work on significant and unique issues where analysis of situations or data requires an evaluation of intangible variables and may impact future concepts, products or technologies.
  
• Familiarity with Python, SQL, AWS, and JIRA.
  
• Familiarity with LLMs, deployment of LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts.
  

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• Applied Statistics, Computer Science, or Engineering or experience in related fields with a focus on machine learning, AI, and LLMs.
  
• Junior category industry experience with responsibility for developing and delivering advanced quantitative, AI/ML, analytical and statistical solutions.
  
• Ability to lead a small team with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization to deliver AI products.
  
• Ability to influence business stakeholders and to drive adoption of AI/ML solutions.
  
• Experience with agile development methodologies, Test-Driven Development (TDD), and product management.
  
• Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business
  
• Demonstrated ability to mentor and operational management of data science team based on project requirements, resourcing requirements, and planning dependencies as appropriate, anticipate risks and bottlenecks and proactively takes actions
  
• Excellent problem solving, communication and collaboration skills, and stakeholder management
  
• Significant experience and/or deep expertise with several of the following:
  
• Machine Learning and AI: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, interpreting and monitoring machine learning models. Expertise in traditional machine learning models (unsupervised, XGBoost, etc.) and Large Language Models (OpenAI, Claude).
  
• Model Deployment: Understanding of model development life cycle, CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness, etc.), A/B testing, and pipeline frameworks such as AWS SageMaker, and newer AWS/Azure Agentic AI infrastructure products.
  
• Data Acquisition and Transformation: Acquiring data from disparate data sources using APIs and SQL. Transform data using SQL and Python. Visualizing data using a diverse tool set including but not limited to Python.
  
• Database Management Systems: Knowledge of how databases are structured and function in order use them efficiently. May include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc.
  
• Data Analysis and Insights: Analyzing structured and unstructured data using data visualization, manipulation, and statistical methods to identify patterns, anomalies, relationships, and trends.
  
• Programming Languages: Python and SQL
  

ProFound Staffing is working with a growing environmental-friendly manufacturing company located in Houston, Texas searching for a Lead Project Engineer (PE) - Mechanical & Fire Protection who can serve as the licensed technical authority on aircraft hangar projects where details matter and excuses don't. This role requires a disciplined PE who leads 65% and 95% designs with confidence, challenges assumptions, and takes ownership of every coordinated submittal package before it reaches the client. If you prefer staying in the background or handing off unresolved redlines, this will feel uncomfortable.

Your work directly impacts hangars that protect F-35s, fifth-generation fighters, and major airline fleets that cannot afford downtime. Missed constructability risks, weak BIM coordination, or sloppy code interpretation don't just create paperwork issues, they delay missions and erode trust.

If the work is done right, you will be instrumental in delivering a fire protection system that safeguards lives, protects aircraft, and prevents environmental damage for the next 50 to 100 years.

Does this level of ownership intimidate you, but at the same time make it irresistible? You might be humble and confident enough for this role.

Travel Requirements:

• Expect travel approximately 1–2 times per month
• Most trips are short (1–2 days) for site visits and client meetings
• Travel may be slightly more frequent during initial onboarding and relationship building
• Travel to client sites in the USA and Canada to support design validation, coordination meetings, and field alignment

Work Schedule:

• This is an onsite position in Houston, Texas.

Education & Professional Licenses:

• Bachelor's degree in Mechanical, Civil, or Fire Protection Engineering
• An active Professional Engineer (PE) license in Mechanical, Civil or Fire Protection Engineering (required)

Requirements:

• 7+ years of experience in aviation, military, or large-scale infrastructure projects
• Direct experience leading design review meetings with sophisticated clients such as NAVFAC, USACE, architect engineering firms, and Canadian Air Force engineering branches
• Strong understanding of building specifications, contract specifications, and relevant building codes such as NFPA standards and UFC criteria
• Experience coordinating multi-discipline design packages (MEP, structural, civil, fire protection)
• Confidence presenting technical solutions in formal 65% and 95% design review meetings
• Experience reviewing and redlining complete engineering submittal packages
• Experience leveraging AI tools ( or ChatGPT) to streamline workflows, with a mindset for adopting new technologies over traditional manual processes

Responsibilities:

• Serve as the technical lead for aircraft hangar projects, ensuring all engineering aspects are executed with precision and completeness
• Lead client design review meetings, including 65% and 95% reviews and redline resolution sessions
• Review and interpret client drawings, specifications, and layouts to guide the development of the company's general arrangement drawings and coordinated submittal packages
• Lead two highly capable junior engineers who prepare design packages and submittals; thoroughly review, refine, and approve their work before client submission
• Propose layout options, pipe routing strategies, and containment tank placement based on each project's structural and operational constraints
• Ensure the company's CAD and Revit models integrate cleanly into client BIM environments
• Identify constructability risks early and translate field lessons into improved design standards
• Support the Project Manager and Installation Manager as the primary technical authority on multiple concurrent projects

This role will naturally evolve into leading a small engineering team over time. While the two junior engineers may not report formally at the beginning, you are expected to function as the technical leader of this group from day one.

Soft Skills:

• Must have a strong verbal and written communication skills.
• Ability to work under pressure and produce results.
• Ability to multi-task and have excellent time management skills.
• Ability to learn quickly and adapt.
• Must have a strong aptitude, attitude and work ethic.
• Flexible to change direction when needed.

Culture and Benefits:

This company has about 85 team members and growing. Their most successful team members connect to their mission, thrive in a fast-paced environment, deliver individual high-quality results as part of a team, and want to do better every day.

This company is a meritocracy. The more value you create, the more benefits in terms of the responsibility you will receive. Successful people at this company see themselves as owners of the company and treat it as such.

• Four weeks of paid vacation. Five weeks after two years of employment and six weeks after four years of employment.
• Health insurance – including company paid premium
• Dental, Vision, and Life insurance options.
• Free CrossFit and Barbell membership
• Stock options package (earned, not given).

About ProFound Staffing:

ProFound Staffing specializes in direct-hire placement of senior professionals across all business functions—from technology, engineering, operations to finance, HR, marketing, and leadership. We help emerging startups and mid-size companies build the strategic talent foundation they need to thrive. We don't just fill positions—we build the teams that drive long-term success.

Business Overview

KINESSO is the technology-driven performance marketing agency providing actionable growth for both our agency partners and clients. We turn 'action' into 'outcome' for our clients, leveraging our unique capabilities in optimization, analytics, AI, and experimentation. KINESSO has brought together the collective power of what was formerly Matterkind, Reprise, P3, and Kinesso under one collective entity that will serve as the most powerful delivery engine in the industry. We have extensive offerings spanning across performance marketing and data and technology. Fueled by a deep understanding of consumer behavior, we offer an end-to-end engine of planning and optimization while also delivering on data-driven strategy for social platforms, actionable growth in e-commerce, and creating curated marketplaces specific to each client's function and needs. The company has more than 6,000 employees operating in more than 60 countries. Learn more at Summary

We are seeking a Staff Software Engineer to spearhead the design and development of a next-generation AI Chat Application that will serve as an enterprise-wide assistant. This application will support a diverse range of organizational functions-including HR, Finance, Business Strategy, Ad Tech, and MarTech-empowering employees with intelligent, context-aware AI capabilities to streamline daily work.

As the Staff Software Engineer, you will guide the technical direction, mentor engineers, and partner with cross-functional teams to deliver a scalable, secure, and high-performing platform.

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• Lead Architecture & Development: Define and implement the architecture for an AI-driven chat platform leveraging Python, GCP, and AI services.
  
• Team Leadership: Mentor and guide a team of engineers, driving technical excellence, collaboration, and delivery.
  
• LLM Integration: Build and optimize solutions with LLM foundational models to support natural language understanding, contextual reasoning, and multi-domain workflows.
  
• Partner with Product Owners: Collaborate closely with product owners to assess technical feasibility, translate business needs into actionable engineering requirements, and ensure alignment with overall product strategy.
  
• Scalability & Reliability: Ensure the system is designed with enterprise-grade security, scalability, and compliance in mind.
  
• Innovation: Explore and adopt emerging practices in prompt engineering, multi-agent coordination (MCP/LLM agents), and applied AI to continuously evolve the platform.
  

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• 12+ years of software engineering experience building production-grade applications.
  
• 7+ years of experience with Java (Python experience strongly preferred).
  
• 3+ years of experience leading or managing engineering teams.
  
• Strong grasp of object-oriented programming, data structures, algorithms, and design patterns.
  
• Experience designing and building scalable APIs (REST, GraphQL, gRPC) and modular, extensible architectures.
  
• Hands-on experience with relational and NoSQL databases (e.g., MSSQL, PostgreSQL, DynamoDB).
  
• Familiarity with messaging and event-driven platforms like Kafka, Temporal for real-time systems.
  
• Strong expertise in GCP and integrating AI services with LLM foundational models.
  
• Experience with AI-powered developer tools (e.g., GitHub Copilot, Claude) to improve productivity and code quality.
  
• Strong troubleshooting, communication, and documentation skills, with a bias for secure, observable, and maintainable solutions.
  
• Comfortable working in Agile/Scrum environments with cross-functional teams.
  

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• Experience with context engineering and fine-tuning AI/LLM outputs.
  
• Familiarity with Model Context Protocol (MCP) for LLM agent orchestration.
  
• Knowledge of LLM agent frameworks for building multi-step, reasoning-driven AI systems.
  
• Experience in enterprise-grade security and compliance frameworks.
  

We offer a Total Rewards package that includes medical and dental coverage, 401(k) plans, flex spending, life insurance, disability, employee discount program, employee stock purchase program and paid family benefits to support you and your family. The salary range for this position is posted below. Where an employee or prospective employee is paid within this range will depend on, among other factors, actual ranges for current/former employees in the subject position, market considerations, budgetary considerations, tenure and standing with the Company (applicable to current employees), as well as the employee's/applicant's skill set, level of experience, and qualifications.

It is the policy of our company to provide equal employment opportunities to all employees and applicants for employment without regard to race, color, ethnicity, gender, age, religion, creed, national origin, sexual orientation, gender identity, marital status, citizenship, genetic information, veteran status, disability, or any other basis prohibited by applicable federal, state, or local law.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

The employer will make reasonable accommodations in compliance with the American with Disabilities Act of 1990. The job description will be reviewed periodically as duties and responsibilities change with business necessity. Essential and other job functions are subject to modification. Reasonable accommodations may be provided to enable individuals with disabilities to perform the essential functions.

For applicants to jobs in the United States: In compliance with the current Americans with Disabilities Act and state and local laws, if you have a disability and would like to request an accommodation to apply for a position with our company, please email .

Content Coordinator & Creator — bayareawilson / bayareaown

Full-Time | Bay Area preferred | Hybrid

About the Role

bayareawilson and bayareaown are two interconnected brands covering Bay Area real estate across YouTube, Instagram, and newsletter. bayareawilson is Wilson Leung's personal brand — a fast-growing YouTube channel and Instagram presence built on data-driven, hyperlocal content. bayareaown is the OWN Real Estate brokerage's social presence, focused on luxury property, market insights, and brand-building for the team.

We're looking for a full-time Content Coordinator & Creator who is AI-native — or actively building those skills — to manage and execute an active multi-format content pipeline across both brands. This role is for someone who sees AI tools as a core part of their workflow, not an afterthought.

What You'll Do

Research & Fact-Checking

• Source and verify market data, development news, and local policy from primary and credible sources before anything reaches a script
• Cross-reference claims across multiple sources and flag outdated or unverifiable information proactively
• Use AI tools to accelerate research workflows without compromising accuracy standards
• Maintain a research-first standard where accuracy is non-negotiable

Content Creation & Writing

• Draft scripts across all active formats for both brands — spanning long-form YouTube, short-form Instagram Reels, luxury property content, and market data posts
• Write multiple hook and title variations per video and support performance testing decisions
• Leverage AI tools to generate drafts, brainstorm angles, and iterate quickly while maintaining consistent brand voice
• Maintain distinct voices across brands — Wilson's is conversational and data-grounded; OWN's is elevated and aspirational

Social Media Management

• Plan and manage the content calendar across both brands
• Schedule and publish Reels, stories, and feed posts for both accounts
• Monitor comments and engagement; flag leads or notable responses for Wilson
• Stay current on Bay Area real estate news to identify timely short-form content opportunities
• Research local events, neighborhood moments, and lifestyle content relevant to each audience

Pipeline & Project Management

• Own the full production pipeline from idea to upload across both brands
• Track all active projects and keep production moving without things falling through the cracks
• Coordinate asset needs — thumbnails, graphics, B-roll lists — and ensure pre-production is complete before filming
• Use AI tools to streamline task management, briefing, and coordination workflows
• Maintain Fair Housing compliance across all published content

Publishing & Analytics

• Manage YouTube upload packages and Instagram scheduling end-to-end
• Monitor performance across both brands and surface patterns in what's working
• Track top-performing formats, hooks, and content types to inform future decisions
• Use AI-assisted analysis to identify trends and optimization opportunities faster

You're a Great Fit If You...

• Have genuine interest in Bay Area real estate, urban development, or local news
• Are obsessive about accuracy and catch errors before they go on camera
• Are AI-native or actively learning — you use tools like Claude, ChatGPT, or Gemini in your daily workflow and are curious about where the technology is heading
• Can write in someone else's voice and understand the difference between a 20-second Reel and a 20-minute YouTube deep dive
• Know how to manage multiple social accounts with different audiences, tones, and purposes
• Have experience in content creation, social media management, or digital marketing — ideally in real estate, finance, or local media
• Are self-directed and thrive in a lean operation with high output expectations
• Based in or deeply familiar with the Bay Area (Peninsula knowledge is a major plus)

Nice to Have

• Hands-on experience with AI tools — Claude, ChatGPT, Gemini, Claude Code, or similar — applied to content, research, or workflow automation
• Real estate industry knowledge or data literacy (market stats, property types, transaction basics)
• Video editing skills
• Instagram Reels strategy experience
• Canva or design tool experience
• Familiarity with Fair Housing law and real estate marketing compliance

What Success Looks Like in 90 Days

• Both brands are posting consistently with no gaps
• The content pipeline is organized and visible — Wilson always knows what's in production and what's next
• Short-form content on both brands reflects the right tone for each audience
• AI tools are actively embedded in the research, writing, and coordination workflow — making the operation faster and sharper
• Wilson spends less time on research, coordination, and scheduling — and more time filming and closing deals

Compensation & Details

• Full-time salaried position
• Bay Area preferred; remote candidates with deep Bay Area knowledge considered
• Competitive salary commensurate with experience and benefits

To apply, send a brief note on why this role interests you, samples of any social accounts, YouTube channels, or content you've worked on, and how you currently use AI tools in your work. Applications without samples will not be reviewed.

OWN Real Estate is an equal opportunity employer.

Are you passionate about Generative AI and want to apply it to one of the most impactful domains — cybersecurity?

Join our cutting-edge startup in the San Francisco Bay Area, where we are developing AI systems that transform how organizations understand, detect, and respond to cyber threats.

As an Applied AI Scientist, you’ll bridge AI research and real-world cybersecurity use cases — designing, implementing, and optimizing models that extract, reason, and act on complex security data.

You’ll work closely with cybersecurity experts, AI infrastructure engineers, and stakeholders to build end-to-end GenAI solutions: from concept to deployment.

This role blends deep applied research with practical engineering, ideal for someone eager to push the limits of Generative AI for meaningful impact.

Why Join Us:

• $25M Seed Funding: Strong capital foundation to innovate and scale fast.
• Early Success: Trusted by Fortune 500 companies, validating real-world demand.
• Experienced Leadership: Founders with 25+ years in cybersecurity — previous ventures valued at $3B+.
• Elite AI Leadership: Heads of AI, Engineering, and Product from world-class tech companies.
• Advanced AI Stack: LLMs, embeddings, RAG systems, LangGraph orchestration, and multimodal AI.
• Competitive Compensation: Excellent salary, meaningful equity, and room for technical leadership growth.
• Cybersecurity Knowledge Preferred but Not Required: We’ll teach you the domain — you bring the AI innovation.

Key Responsibilities:

Core Applied AI Research

• Collaborate with cybersecurity researchers and stakeholders to scope AI-driven solutions to security problems (e.g., vulnerability management, code analysis, threat detection).
• Conduct applied research using the latest LLMs and embedding models (Claude, Google GenAI, Unsloth, vLLM).
• Prototype, fine-tune, and evaluate GenAI and RAG/CAG architectures for classification, summarization, reasoning, and context synthesis.
• Perform embedding-level optimization for text, code, and image data using Unsloth, Hugging Face, Voyage, or similar frameworks.

System Development & Integration

• Develop and test end-to-end AI pipelines integrating Milvus or Pinecone for semantic retrieval.
• Build agentic AI systems using LangGraph or similar frameworks to enable autonomous reasoning and task chaining.
• Collaborate with MLOps engineers to deploy and monitor AI models in production securely and efficiently.
• Contribute to synthetic data generation pipelines for fine-tuning and evaluation.

Evaluation & Optimization

• Implement evaluation frameworks using DeepEval and GenAI tools (Claude / Google GenAI) for factuality, reliability, and robustness.
• Optimize model performance across latency, accuracy, and cost using vLLM, quantization, or caching strategies.
• Maintain reproducible experiment tracking with MLflow, Weights & Biases, or internal tools.

Innovation & Leadership

• Stay ahead of GenAI trends — multi-modal reasoning, agentic orchestration, embedding adaptation.
• Explore hybrid LLM deployment strategies (local Unsloth/vLLM + cloud APIs like Claude, Google GenAI).
• Document best practices, share learnings, and mentor junior scientists on applied GenAI workflows.

Qualifications:

Required

• 4+ years in Applied AI / Machine Learning Research / Data Science.
• Strong understanding of LLMs, embeddings, RAG systems, and multimodal learning.
• Proficiency in Python and frameworks like PyTorch, Transformers, Hugging Face, or LangChain.
• Experience in prompt engineering, model evaluation, and retrieval-based reasoning.
• Hands-on experience with vector databases (Milvus / Pinecone) and orchestration frameworks (LangGraph / LangChain).
• Strong communication skills and ability to collaborate across research and engineering functions.

Preferred

• Experience with fine-tuning LLMs or embeddings using Unsloth or similar frameworks.
• Familiarity with Claude / Google GenAI APIs for cloud-based inference and evaluation.
• Exposure to cybersecurity or enterprise data (CVEs, pluginText, network or asset logs).
• Prior work on synthetic data generation and evaluation frameworks (DeepEval).
• Experience in a fast-paced startup or applied research environment.

Our Culture & Team

• Collaborative and Mission-Driven: Every project directly advances global cybersecurity.

• World-Class Mentorship: Work with senior experts from top AI and security companies.

• Growth-Oriented: Opportunities to lead GenAI initiatives and own major research tracks.

• Inclusive and Innovative: We value diverse perspectives and open experimentation.

Perks & Benefits

• Comprehensive medical, dental, and vision coverage.
• Wellness and professional development stipends.
• Equity options — your impact equals ownership.
• Access to state-of-the-art GPUs, APIs, and GenAI frameworks.

We're winning quickly.

• 
  
• We’re backed by Accel, by the same partner who led the series A for Scale, Vercel, and Sentry. We launched out of stealth 2 months ago (TechCrunch), and are already powering pages that generate hundreds of thousands of dollars in pipeline. Also recently featured on CNBC.
  

We're drowning in demand.

• 
  
• Flint has thousands of companies on our waitlist with many coming inbound every day. The market has spoken. We're growing our team so we can stop turning away customers.
  

Recognized names that turn heads.

• 
  
• We've earned the trust of customers like Cognition, Reducto, Graphite, Tandem, and more.
  

Flint is defining the next generation of websites: ones that can constantly build and optimize themselves based on visitor behavior and market changes. Today, we deliver on-brand landing pages on your domain fast, without any rebuilds or engineers. We are backed by Accel, Sheryl Sandberg (former Meta COO)'s venture fund SBVP, and Neo.

Sandberg instantly understood Flint's vision. "I was sharing how it took (me) five teams three months to build one A/B test just to increase conversion by 10% on our Google ad," Lim said. "And then she stopped me, [and] said, 'Michelle, it was 140 people at Meta who had to do this'." — TechCrunch

Imagine a world where your website launches new pages, tests creative, and optimizes performance entirely autonomously. Just as autonomous vehicles respond to real-world inputs like road conditions and traffic patterns, Flint-powered websites respond to external signals such as competitive shifts, user behavior, and trending search queries.

"One of the most talent-dense AI startups... each member of the early Flint team has a track record, and as a team, they perform like athletes. Amazing to watch." - Dan Levine, Accel

Flint is led by co-founders Michelle Lim, Engineer #1 turned Head of Growth and Product at Warp, and Max Levenson, engineering leadership at autonomous vehicle startup Nuro, then Engineer #2 at Vooma (YCS23). Our founding designer Leona Hudelson was previously head of Growth Design at Netflix in charge of optimizing 1B+ visits to .

Companies have used Flint to hit goals like…

• 
  
• Ranking #1 on AI answer engines like ChatGPT, Perplexity and Google AI Overview
  
• Driving 50% higher ad conversion rates on Google Ads months ahead of schedule
  
• Generating 7 figures of ARR
  

The first version of Flint's autonomous website platform produces on-brand landing pages from content briefs and prompts in minutes. Flint ingests a company's existing design system (components, brand guidelines, and visual tokens), then generates fully-coded landing pages that live on the customer's top-level domain, on a subfolder at URLs like /campaign-name

We're looking for a founding marketing lead to build Flint's marketing engine and establish Flint as the de facto brand for marketing websites.

As Founding Marketing Lead, you'll be THE marketer at a marketing company. Your opinions will deeply shape the product. This is a rare opportunity to shape how marketers think about AI, websites, and GTM while building Flint's growth engine from the ground up.

Flint has already run a successful product launch such as the out-of-stealth launch, been covered by Techcrunch, CNBC, and Business Insider, hosted in-person events like Growth Craft, and is crushing it on founder-led socials. Your job is to build on this momentum with the CEO and turn Flint into the biggest brand in the space.

• 
  
• Lead product launches: Own the launch for new features and releases, from messaging to rollout.
  
• Define brand and positioning: Own Flint's messaging frameworks, positioning docs, and brand voice as we create the autonomous website category.
  
• Lead content that teaches: Create use-case playbooks, example prompts, tutorials, case studies, and demos that help marketers get value from Flint. Drive self‑serve activation and early‑user success.
  
• Build and scale partnerships: Partner with design agencies, develop affiliate programs, and build integrations with GTM tools like Clay.
  
• Own sales enablement: Create the materials, decks, case studies, and resources that help prospects succeed with Flint
  
• Be the voice of Flint: Edit and publish LinkedIn content weekly and lead newsletters and events.
  
• Build and maintain our marketing website and docs: Ensure Flint's web presence is as sharp and innovative as our product.
  
• Surface product feedback: Work cross‑functionally with Product and Engineering to relay customer friction and shape the roadmap.
  
• Build the marketing team: As Flint scales, help hire and manage marketers.
  

• 
  
• Strong writing and storytelling chops: you can distill complex ideas into crisp, compelling messaging.
  
• You're the kind of person who would be a power user of Flint, and if you're not yet, you're excited to make it happen.
  
• 4+ YoE in B2B SaaS growth or product marketing with hands‑on execution, ideally at a fast‑paced startup.
  
• Bias for doing, not just strategizing. You ship content, run experiments, and iterate quickly.
  
• Strong content and education skills: you can create tutorials, webinars, and docs that actually help people.
  
• Practical SEO and paid acquisition experience, acquired either directly or adjacent to the function.
  
• Comfortable on camera.
  
• Data‑driven: you can set and report on traffic and conversion.
  
• Bring a founder's mindset to your work: be proactive, resourceful, and comfortable operating without a playbook.
  

• 
  
• Enthusiasm for Claude Code and AI‑native marketing workflows: you believe this is the future and want to be at the forefront.
  
• Comfortable with product tooling and integrations (APIs, Zapier, Clay‑like automations).
  
• PMM or devrel‑like background: ability to demo product and create sample templates.
  
• Experience with marketing automation or sales enablement tools (HubSpot, Notion, etc.).
  
• Familiarity with design systems or Webflow workflows.