Shield Ai Address Jobs in Usa

** We will only consider applicants who are currently residing in South Florida**

About MMG

MMG Equity Partners is a Miami-based, family-led real estate investment and development platform with a portfolio of retail shopping centers across South Florida. Beyond the real estate business, MMG operates a private family office that manages investments, insurance, and financial reporting across multiple entities and family members. MMG separately owns Tamarack Resort in Idaho. We are a flat, fast-moving organization where you will work directly with principals — not layers of management.

This is a ground-floor role. We are building the function from scratch. The right person will define what AI means at MMG, then build it.

The Role

The Director of AI Initiatives & Adoption is responsible for identifying, implementing, and managing AI tools and systems that meaningfully improve how MMG operates across real estate and family office functions. Every project you take on must connect to a business outcome — faster decisions, better data, more deals, reduced overhead.

You will own four things: identifying where AI creates real value at MMG, building or procuring the tools to capture that value, driving adoption across the team and continuously improving how those tools are used, and ensuring the systems are secure and maintainable. Implementation without adoption is not success.

• Reports to Managing Director
• Direct reports - contractors and freelancers as needed
• Current IT Enviroment - outsourced IT for network support

Current Tech Stack (what you are walking into)

You need to understand these systems deeply. Part of your job is figuring out how to connect them and leverage AI to make us more productive/competitive

What you will work on

Below are four areas where we believe AI creates the nearest near-term value at MMG. You first job is to work with the leaders in each area to assess each, prioritize, and build a 6-month roadmap. In addition to the below, the right individual will identify a myriad of other AI use cases to add value and reduce repetitive tasks.

1. Leasing and Tenant Prospecting

MMG owns retail shopping centers and is responsible for filling vacancies with the right tenants – while we work with third party leasing firms, we wish to supplement their efforts by generating direct leads.

• Design and build AI scraping tools to compile databases of South Florida retailers and service businesses for targeted uses
• Build a tool to identify prospective uses/tenants: given a vacancy (size, location, co-tenancy, demographics), which business types and specific operators are the best candidates?
• Design and build AI-assisted leasing outreach workflow: targeted uses identified for vacancies → database queried → outreach drafted and sent → responses tracked in Dynamics (or other CRM)
• Activate Microsoft Dynamics (or other) as the CRM for online leasing
• Identify tools or workflows to monitor existing tenant health (sales reporting, foot traffic, business review signals) to get ahead of vacancies before they happen
• Identify and implement AI-assisted lease abstracting tool to best fit our environment

2. Real Estate Acquisitions

MMG evaluates potential acquisitions across South Florida. Today this process is manual and dependent on individual knowledge. AI can accelerate every stage.

• Design and build AI scraping tools to compile databases of South Florida real estate owners
• Build an AI-assisted underwriting workflow that pulls property data, comps, and market context into a structured analysis template
• Identify AI tools for market intelligence — rent growth trends, cap rate movements, retail category performance by submarket
• Evaluate AI-powered deal sourcing tools (e.g. CoStar integrations, off-market sourcing platforms

3. Private Family Office

MMG's family office manages investments, insurance, and financial reporting for family members. This is a sensitive area requiring strict data governance — but it also has high-value AI applications.

• Addepar AI integration: explore ways to use AI to generate plain-language investment performance summaries and financial reports from Addepar data, reducing manual reporting time
• Insurance management: build a structured database or AI assistant for tracking insurance policies (G/L, personal property, family member policies) with renewal alerts and coverage gap analysis
• Document intelligence: connect family office files in SharePoint to an AI interface for on-demand retrieval of partnership agreements, tax documents, and legal filings
• Evaluate data governance and access controls for family office data — this is sensitive personal and financial information; AI access must be role-based and audited

IT Infrastructure and Security

You are not a network administrator — we have an outsourced IT firm for that. But you are responsible for AI governance at MMG: ensuring every AI tool introduced into the environment meets a clear security and accountability standard.  Practically, this means:

• Evaluating AI vendors for data handling practices — what data leaves our environment, where it is stored, and how it is used for model training
• Defining and enforcing a data classification policy: what information can be sent to external AI APIs, what must stay on-premise or in private cloud environments
• Working with IT firm to ensure AI tools are deployed within the MS365/Azure security perimeter where possible
• Evaluating the Claude Teams → Claude Enterprise migration and the Microsoft Connector configuration for SharePoint access — specifically, controlling which documents are accessible to AI and by which users
• Vetting any third-party AI integrations (i.e. ZoomInfo, Yardi, etc.) for compliance with firm data policies

Prompt Library & AI Adoption

Building the tools is only half the job. The other half is making sure the team actually uses them — and uses them well. This requires two ongoing responsibilities that most AI roles underestimate.

Prompt Library

You will build and maintain a living prompt library — a curated set of tested, optimized prompts for every recurring AI task at MMG. Examples include: underwriting analysis from a rent roll, lease abstraction for a specific clause type, tenant outreach drafts by use category, and insurance renewal gap analysis. The library lives in SharePoint, is accessible to the full team, and is updated continuously based on user feedback and evolving business needs. A well-maintained prompt library is what turns AI from a tool that one person uses well into a capability that the whole organization depends on.

Adoption Monitoring & Continuous Improvement

You are responsible for whether AI tools actually get used — not just whether they get deployed. This means tracking adoption across the team, identifying where workflows are not sticking, providing training and troubleshooting support to staff using AI tools, and iterating on both the tools and the prompts based on real usage patterns. You will serve as the primary internal resource for the team when they hit limitations or need guidance on how to get better outputs. Deployment without adoption is a sunk cost.

What we are looking for

Required:

• 3–6 years of experience in data, technology, or AI — ideally in a context where you had to figure things out without a large team around you
• Hands-on experience with AI tools and LLM platforms — not just using them, but building workflows, prompts, and integrations on top of them
• Demonstrated ability to connect AI capabilities to specific business outcomes (not just technology for its own sake)
• Comfort with the Microsoft 365 ecosystem — SharePoint, Dynamics, Teams, Azure
• Ability to manage and direct contractors and developers without being the one writing all the code
• Non-technical stakeholder communication — you will regularly present AI recommendations, tool evaluations, and implementation roadmaps directly to the principal(s) who are real estate operators, not technologists. The ability to translate AI capabilities into business outcomes (not feature lists) is non-negotiable. If you cannot explain why a tool matters in terms of time saved, deals sourced, or risk avoided, you will not be effective in this role
• In-office presence at Pinecrest HQ is required initially (possible hybrid in the future)

Preferred

• Experience in commercial real estate, property management, or a related field
• Familiarity with Yardi, Addepar, or similar platforms
• Background that includes both technical work (building things) and strategic work (recommending what to build)
• Experience implementing AI in a small-team / resource-constrained environment

GENERAL SUMMARY:

The Manager of AI Enablement (Senior) leads the development and execution of Element Care’s internal approach to artificial intelligence. This role defines AI standards, policies, and best practices while enabling staff across the organization to adopt AI safely, ethically, and effectively. Reporting to the IT department, this position acts as a trusted advisor to leaders and end users, shaping AI governance, vendor strategy, training, and enterprise enablement.

ESSENTIAL RESPONSIBILITIES:

•    Define and maintain organizational AI standards, policies, and governance frameworks.

•    Lead the deployment of off-the-shelf AI solutions, including ambient documentation, predictive analytics, administrative automation, and clinical decision support tools.

•    Enable responsible use of generative AI across administrative and operational functions.

•    Conduct continuous workflow analysis to identify automation and AI-enablement opportunities.

•    Evaluate AI and AI/ML models, tools, and vendor solutions for suitability, risk, and value.

•    Partner with IT, data, analytics, and platform teams to align AI initiatives with enterprise architecture.

•    Provide oversight and guidance on AI-enabled workflows, automation, and agent capabilities.

•    Measure, monitor, and report on AI initiative outcomes, value realization, and performance.

•    Build business cases and recommendations for future AI investments.

•    Serve as the primary advisor to leaders and teams on AI use cases, risks, and governance.

•    Monitor regulatory, ethical, and industry developments related to AI.

•    Help establish and mature a scalable AI enablement and governance operating model.

•    Influence adoption and consistency without direct authority.

•    Perform other duties as assigned.

JOB SPECIFICATION:

•    6–10+ years of relevant professional experience, including applied AI, automation, analytics, or emerging technology leadership.

•    Demonstrated experience evaluating AI/ML models, vendor solutions, or AI platforms.

•    Experience with vendor management, solution selection, or hands-on implementation required.

•    Demonstrated experience defining standards, policies, or enterprise enablement programs.

•    Healthcare or other regulated industry experience strongly preferred.

•    Strong understanding of applied AI, AI/ML evaluation, governance, risk, and ethical considerations.

•    Ability to translate complex concepts into practical organizational guidance.

•    Experience developing business cases and value narratives for technology investments.

•    Executive-level communication and facilitation skills.

•    Proven ability to operate independently and influence across the enterprise.

•    Strategic mindset with a pragmatic, implementation-oriented approach.

Compensation details: 13 Yearly Salary

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At Rite-Hite, your work makes an impact. As the global leader in loading dock and door equipment, we design and deliver solutions that keep our customers safe, secure, and productive. Here, you'll find innovation, stability, and the chance to grow your career as part of a team that's always looking ahead.

Rite-Hite is a global leader in industrial safety and efficiency solutions. As part of our digital transformation journey, we are seeking a Systems Architect, Edge AI/ML to help build and scale intelligent systems that deliver real-time insights, automation support, and customer value at the edge of industrial environments.

The Systems Architect, Edge AI/ML is responsible for defining and guiding the architecture for artificial intelligence and machine learning deployed on devices and edge platforms. This role ensures that AI/ML solutions are scalable, reliable, secure, and aligned with enterprise product and platform objectives.

The architect partners closely with product management, device and edge software teams, data and cloud teams, and digital solution leaders to translate business and customer requirements into robust AI/ML foundations that enable consistent behavior, efficient lifecycle management, and high-quality user experiences across industrial environments.

CORE RESPONSIBILITIES

• Define and maintain reference architectures, design patterns, and standards for deploying AI and ML models on edge devices and platforms.
• Establish common approaches for data ingestion, feature pipelines, model inference, performance optimization, and lifecycle management at the edge.
• Ensure architectural decisions support real-time operation, scalability, reliability, safety, and security.

• Drive the strategic use of AI and ML at the edge by establishing repeatable patterns for model development, deployment, monitoring, and update.
• Own a portion of the internal technology radar related to AI/ML, edge analytics, and sensing technologies.
• Foster a culture of responsible, ethical, and transparent AI practices aligned with cybersecurity, privacy, and safety requirements.

• Partner with product management and engineering teams to enable AI-driven capabilities such as condition monitoring, vision-based sensing, anomaly detection, and predictive insights.
• Guide architectural decisions related to edge compute constraints, sensor integration, and real-time inference workloads.
• Promote reuse and consistency of AI/ML components across products and platforms.

• Define patterns for integration between edge AI/ML solutions, device software, hybrid mobile applications, and enterprise or cloud-based platforms.
• Ensure solutions support online, offline, and hybrid deployment models common in industrial environments.
• Promote interoperability with internal systems and approved third-party technologies.

• Define secure-by-design and safety-aligned principles for AI/ML model deployment and operation at the edge.
• Ensure alignment with applicable safety, quality, and industrial cybersecurity standards.
• Participate in architecture and design reviews to assess risk, resilience, and compliance.

• Collaborate across product management, device and edge software, data science, cloud platforms, manufacturing, service, and mobile application teams.
• Provide technical leadership, mentorship, and guidance to engineers and teams working with AI/ML technologies.
• Serve as a technical advisor in strategic customer conversations and enterprise implementations when appropriate.

• This role does not have direct reports but is expected to provide technical leadership and architectural guidance across multiple teams.

QUALIFICATIONS

Education & Experience

• Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, Data Science, or a related technical field required; Master's degree preferred.
• 8+ years of experience delivering AI/ML-enabled solutions, with demonstrated experience deploying models in edge or resource-constrained environments.
• Experience with industrial, connected, or safety-critical systems preferred.

Knowledge / Skill Requirements

• Strong understanding of AI/ML architectures, model lifecycle management, and real-time inference at the edge.
• Experience designing systems that balance performance, accuracy, latency, and resource constraints.
• Ability to think systemically across sensors, devices, edge platforms, mobile applications, and cloud services.
• Strong communication skills and ability to influence cross-functional stakeholders.
• Familiarity with industrial automation, IoT ecosystems, or computer vision is a plus.

Leadership & Collaboration:

• Visionary technical leader who can inspire cross-functional teams and align stakeholders to a shared product vision.
• Exceptional communicator across technical and non-technical audiences.
• Committed to data-driven decision-making and delivery excellence.

Why Join Rite-Hite Digital Solutions?

As a technology leader within a globally trusted industrial brand, you will play a pivotal role in shaping how AI and machine learning are applied safely and effectively in real-world environments. Your work will help customers improve safety, productivity, and uptime through intelligent, edge-driven solutions that deliver measurable operational impact.

What We Offer

At Rite-Hite, we take care of our people - because when you're supported, you can do your best work. Our benefits are designed to support your health, your future and your life outside of work:

• Health & Well-being: Comprehensive medical, dental, and vision coverage, plus life and disability insurance. A robust well-being program with an opportunity to receive an extra day off and more.

• Financial Security: A strong retirement savings program with 401(k), company match, and profit sharing.

• Time for You: Paid holidays, vacation time, and personal/sick days each year.

Join us and build a career where you're supported - at work and beyond.

Rite-Hite is proud to be an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under federal, state, or local law.In accordance with VEVRAA, we are committed to providing equal employment opportunities for protected veterans.We are also committed to maintaining a drug-free workplace for the safety of our employees and customers.

• 
  
• 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.
  

• 
  
• 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
  

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

• 
  
• 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).
  

• 
  
• 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.
  

Hands-On Product Manager — AI-Native Recruiting Platform (HireHQ)

Build the AI operating system for recruiting.

HireHQ is building the next generation AI-native recruiting platform — one that eliminates manual recruiter workflows and replaces them with intelligent automation, AI copilots, and decision intelligence.

Traditional ATS platforms were built for record keeping.

HireHQ is building a recruiting operating system that helps companies find, evaluate, and hire the best talent faster.

We are looking for a highly hands-on Product Manager who can help design and ship this future.

This is not a traditional PM role. You won’t just write tickets and manage roadmaps.

You will:

• Prototype product ideas yourself
• Use AI tools to rapidly build concepts
• Work directly with engineers
• Drive automation across recruiting workflows
• Ship AI-native features quickly

If you like building products at the intersection of AI, automation, and recruiting, you’ll thrive here.

What You'll Work On

You’ll help build core capabilities of the HireHQ recruiting platform, including:

AI Candidate Discovery

• AI-powered candidate search
• Intelligent candidate matching
• Automated candidate enrichment
• Talent graph and candidate insights

AI Screening & Evaluation

• Resume and profile understanding
• AI candidate scoring and ranking
• Interview intelligence and summarization
• Automated screening workflows

Recruiter Copilots

• AI recruiter assistants
• Automated outreach generation
• Pipeline prioritization
• Smart next-action recommendations

Candidate Experience

• AI-powered communication
• Automated follow-ups
• Interview scheduling automation
• Candidate journey insights

Recruiting Automation

• Workflow orchestration across the hiring pipeline
• Intelligent routing and task automation
• AI-driven pipeline management
• Recruiter productivity tools

Our goal is simple:

Reduce manual recruiting work by 80% while improving hiring outcomes.

What You'll Actually Do

You will operate like a product builder.

Ship Products

• Own product areas end-to-end
• Work directly with engineers to design solutions
• Move from idea → prototype → shipped feature quickly

Prototype With AI

You’ll actively use tools like:

• Cursor
• GitHub Copilot
• Claude
• ChatGPT
• Figma

to rapidly create:

• product mockups
• workflows
• prototypes
• PRDs
• user stories
• experimentation plans

We expect PMs to use AI as a force multiplier, not just write docs.

Design AI-Native Workflows

You'll help design product systems that use:

• LLMs
• semantic search
• embeddings
• candidate matching
• summarization
• automation engines

to eliminate manual recruiting work.

Drive Automation

You will constantly ask:

"Why is a human doing this?"

Then build systems that automate it.

Work Extremely Closely With Engineering

You will collaborate daily with engineers to:

• shape product architecture
• refine technical tradeoffs
• ship features quickly
• iterate with real customer feedback

What We're Looking For

Experience

• 5+ years in product management
• Experience building recruiting or HR tech products

Examples include:

• Applicant Tracking Systems (ATS)
• Recruiting CRM platforms
• Candidate engagement tools
• Talent sourcing platforms
• Interview platforms
• Talent intelligence platforms

You deeply understand how recruiting actually works.

AI Product Thinking

You’ve helped build or design AI-enabled product capabilities, such as:

• candidate matching
• screening automation
• workflow automation
• recommendation systems
• AI copilots
• search and ranking systems

Builder Mindset

You like creating things, not just planning them.

You are comfortable:

• prototyping ideas
• creating workflows
• building product concepts independently
• using AI tools to accelerate execution

Comfort With Ambiguity

This is a startup environment.

You should enjoy:

• fast iteration
• unclear problems
• ownership
• shipping quickly

Strong Candidates Often

• Previously worked at HR tech or recruiting tech companies
• Have built ATS or recruiting workflow products
• Use AI tools daily for product development
• Think about automation and workflow intelligence
• Care deeply about shipping useful products quickly

What Success Looks Like

Within your first 3 months:

• Recruiters using HireHQ spend dramatically less time on manual tasks
• AI features automate key recruiting workflows
• Customers rely on AI insights to prioritize candidates
• Recruiters move from administrative work → strategic hiring

Why This Role Is Different

Most recruiting software was designed 15–20 years ago.

HireHQ is rebuilding recruiting software from the ground up using:

• AI agents
• workflow automation
• intelligent candidate matching
• recruiter copilots

This role is an opportunity to help build the AI operating system for hiring.

AI Innovation Architect

Location: Hybrid; Ashburn, VA; Springfield, VA; Washington, D.C.

Clearance: U.S. Citizen; Must have an active Top-Secret Clearance or DHS Public Trust Clearance.

InDev is seeking a senior strategic and technical AI Architect responsible for designing, building, and deploying artificial intelligence solutions that support mission outcomes across the homeland security market. In this role you will bridge advanced AI capabilities - including machine learning, natural language processing, and data engineering - with operational requirements, ensuring solutions are secure, scalable, and aligned with the homeland security mission.

YOUR FUTURE DUTIES AND RESPONSIBILITIES

• Define overall system architecture, selecting and governing Artificial Intelligence / Machine Learning (AI/ML) and platform technologies, and ensuring solutions are scalable, secure, and production-ready
• Lead end-to-end technical design, development, and implementation of an agentic AI system to orchestrate user queries across enterprise data sources
• Partner closely with development, DevOps and data engineering teams to translate project requirements into an extensible AI architecture
• Create and promote AI strategies that align with business objectives
• Develop and coordinate POCs to test new technologies
• Evaluate and select appropriate AI tools, frameworks, and platforms (i.e., AWS, Azure, Google) to drive innovation

QUALIFICATIONS

• U.S. Citizen; Active Top-Secret Clearance or DHS Public Trust Clearance
• 8+ years of experience delivering AI solutions across federal agencies
• Bachelor’s degree in Computer Science, Engineering, or Data Science
• Deep understanding of machine learning (ML), deep learning, Natural Language Processing (NLP), and neural networks
• Experience with cloud platforms (AWS, Google Cloud, Azure) and container orchestration tools like Kubernetes and Docker
• Ability to identify high-impact AI use cases and translate them into technical requirements
• Experience designing, building, and deploying advanced AI systems including Generative AI, AI Agents, LLMs, Reinforcement Learning, and computer vision models
• Ability to apply cloud and engineering expertise across AWS, GCP, Kubernetes, Docker, Terraform, Helm, Linux, and AI services, such as SageMaker, Vertex AI, Bedrock, or Gemini
• Experience with Python, agent frameworks, data engineering, APIs/microservices, vector databases, SQL engines, distributed systems, cloud services, RAG
• Experience developing and maintaining AI/ML roadmaps, performing Analysis of Alternatives, and making defensible technical tradeoff decisions
• Experience leading multidisciplinary teams, including data scientists, engineers, and business stakeholders
• Excellent written and oral communication skills
• Ability to tailor and present information across multiple stakeholders

NICE TO HAVES

• Experience integrating AI solutions with SaaS/PaaS platforms (e.g., ServiceNow, Salesforce, etc.)
• Experience implementing virtual agents within SaaS/PaaS platforms (e.g., ServiceNow Virtual Agent, Salesforce Agentforce, etc.)
• Experience with Google Gemini

ABOUT US

At InDev, we’re not just a company; we’re a trailblazing force transforming the way data shapes the future. As a dynamic player in the federal government sector, we’re on a mission to empower agencies with cutting-edge data solutions that drive innovation, efficiency, and progress. Our team thrives on collaboration, innovation, and embracing challenges head-on to create a meaningful impact on the world around us.

WHY INDEV

• Innovative Environment: Join a team that thrives on creativity and innovation, where your ideas are not only heard but encouraged.
• Meaningful Impact: Contribute to projects that directly impact federal agencies, driving positive change on a national scale.
• Dynamic Collaboration: Work alongside diverse experts who are passionate about pushing boundaries and making a difference.
• Agile Mindset: Embrace Agile methodologies that encourage flexibility, adaptability, and rapid growth.
• Learning Culture: Enjoy ongoing learning opportunities and professional development to expand your skill set.
• Cutting-edge Tech: Engage with the latest technologies and tools in the data integration landscape.

If you’re ready to embark on a journey of innovation, collaboration, and impact, InDev welcomes you to join our team. Let’s shape the future together.

Director of AI

Location: Chicago, IL (Remote Eligible – must be US based)

Salary: $250,000 – 280,000 base + bonus

We’re partnering with a global education technology company undergoing a major transformation from a traditional publisher into a data and AI driven digital learning platform. The organization is investing heavily in AI and advanced data capabilities to deliver personalized learning experiences at global scale.

They are hiring a Director of AI to lead a team of AI researchers and data scientists responsible for developing and deploying advanced machine learning and Generative AI solutions across the enterprise.

The Role:

This is a highly strategic role that combines technical leadership, team management, and hands-on architectural oversight. The Director of AI will help define the long-term AI roadmap while working closely with product, engineering, and business stakeholders to bring production AI systems to life.

What you’ll do:

• Lead and grow a team of AI researchers and data scientists, providing technical mentorship and career development
• Define and execute the AI strategy and roadmap, with a strong focus on Generative AI capabilities
• Partner with product, engineering, and business teams to identify high-impact AI opportunities
• Oversee the design, development, and deployment of production-grade AI and ML systems
• Translate complex technical work into clear insights for both technical and executive stakeholders
• Manage project timelines, priorities, and team resources to ensure successful delivery of AI initiatives

What They’re Looking For

• PhD in Artificial Intelligence, Data Science, Computer Science, or a related technical field
• 8+ years of experience in AI, machine learning, or data science
• Proven experience leading teams of AI researchers or data scientists
• Deep expertise in machine learning, AI systems, and Generative AI technologies
• Strong communication skills with the ability to present technical concepts to senior leadership
• Experience collaborating cross-functionally with product, engineering, and business teams

Nice to Have

• Experience deploying Generative AI solutions in production environments
• Experience working in large-scale technology or digital product organizations
• Exposure to education technology or learning platforms

This role offers the opportunity to shape the AI strategy for a global platform impacting millions of learners worldwide, while leading a highly technical team working on cutting-edge machine learning systems.

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.

**Candidate must be willing to go into office 3 days a week**

Senior Full-Stack AI & Data Engineer – Contract

RBA is an established leader and trusted partner for enterprise and mid-size organizations seeking to transform their business through technology solutions. As a Digital and Technology consultancy, we combine strategic insight with technical expertise to deliver impactful, scalable solutions that align with business goals. We take pride in working with some of the most recognized companies in our market—while fostering a culture that blends challenging career opportunities with a collaborative, fun work environment.

We are seeking a Senior Full-Stack AI & Data Engineer to join our growing Data & AI practice, supporting a high-impact client. In this role, you will lead the design and development of end-to-end AI-powered applications that drive personalization, predictive analytics, and next-generation digital experiences.

You’ll partner with business stakeholders, product teams, and engineers to build production-grade AI solutions—from data pipelines and model development to APIs and user-facing applications. The ideal candidate brings deep expertise across the full stack, modern data platforms, and generative AI technologies, with a passion for solving complex business challenges through innovative solutions.

Responsibilities

• Design and develop end-to-end AI-powered applications, including backend APIs and user-facing interfaces, to enable scalable and intuitive AI solutions.
• Build and maintain robust APIs using technologies such as Node.js, NestJS, or FastAPI, and develop modern web applications using React or similar frameworks.
• Develop, fine-tune, and deploy machine learning models using frameworks such as PyTorch and Scikit-learn.
• Implement advanced generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines and multi-modal AI applications.
• Design and build agentic AI systems using frameworks such as LangChain, enabling multi-step reasoning, tool use, and automation.
• Architect and optimize end-to-end data pipelines (ETL/ELT) using Python, SQL, and orchestration tools such as Airflow.
• Manage and integrate data workflows within Snowflake, leveraging technologies such as Snowpark or Cortex.
• Implement monitoring and observability for AI systems, including tracking model performance, drift, latency, and reliability.
• Design and deploy cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines across AWS, Azure, or GCP.
• Collaborate with business stakeholders to translate data into actionable insights and intelligent applications.
• Contribute to DevOps best practices, including infrastructure-as-code (Terraform) and automated testing.
• Mentor junior engineers and promote best practices in AI ethics, data governance, and code quality.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience across full-stack development, including backend (Node.js/Python) and frontend frameworks (React or similar).
• Strong experience designing and building data pipelines and modern data platforms, including expertise in SQL and data modeling.
• Proven experience deploying AI/ML solutions in production environments, including MLOps and model lifecycle management.
• Hands-on experience with generative AI technologies, including LLMs, prompt engineering, and RAG architectures.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of DevOps practices, including CI/CD, containerization, and infrastructure-as-code (Terraform).
• Excellent communication skills and ability to work effectively in client-facing environments.

Preferred Qualifications

• Experience with Snowflake, including Snowpark, Cortex, or similar data platform capabilities.
• Experience building agent-based AI systems or working with frameworks such as LangChain.
• Familiarity with vector databases and semantic search architectures.
• Experience developing mobile applications using React Native or Flutter.
• Knowledge of mobile architecture, UI/UX principles, and API integration patterns.
• Experience deploying applications to Apple App Store or Google Play Store.
• Familiarity with security and authentication protocols, including OAuth2, biometric authentication, and secure data handling.
• Cloud or data platform certifications (AWS, Azure, GCP, Snowflake, or similar).

Leadership & Culture

• Demonstrate leadership through mentorship, technical guidance, and promoting engineering best practices.
• Balance innovation with pragmatism—able to work across cutting-edge AI solutions and foundational data engineering tasks.
• Thrive in a collaborative, fast-paced consulting environment with a strong focus on client impact and delivery excellence.

AI Strategist

Senior Director, Consulting & Delivery

Level & Department

The honest version of what's happening in enterprise AI in the middle market ($100M - $2B) right now is messy. Most organizations know they need to move. Very few have the leadership that can operate fluently at both ends of the problem… the C-suite conversation about investment rationale and the engineering conversation about whether the architecture can actually support what was just promised.

That gap is expensive and we've seen it in every sector we work in. It shows up the same way every time: smart strategy work that doesn't connect to anything deployable, or capable technical teams building things that never get funded or adopted.

The Principal AI Strategist role exists to close that gap on our most important engagements.

THE ROLE

What this position actually does

You are the senior-most strategy and delivery mind on a client engagement. You hold the intellectual and commercial thread across the entire lifecycle from the first diagnostic conversation through to a working AI system in production and the expansion that follows when the client realizes it's changing something real.

You are not the person who manages the team to do the thinking… you are responsible for the most strategic form of that thinking. You shape the strategy, challenge the architecture, own the executive relationship, and are personally accountable for whether the engagement creates measurable business value.

The title is Principal AI Strategist because that's the actual job. The level is Senior Director because that reflects the scope, accountability, and authority this role carries inside Quantum Rise and in front of clients.

OUR OPERATING PRINCIPLES

The intellectual framework you'll work inside

Quantum Rise operates from a set of principles we call Consulting 2.0. They define how engagements are structured, how we challenge client assumptions, and what we hold ourselves accountable to.

Think like an investor, not a technologist

AI value is relative to each client’s own goals / circumstances and capital is precious. We anchor every engagement to strategy → value streams → enterprise value. We don't start with use cases. We start with where the business makes and loses money, and work backward to where AI creates leverage.

• Map to where the work actually happens: We go to L4–L5 process depth where the task-level execution that explains KPI performance and reveals where AI readiness actually exists.
• Diagnose before prescribing: We use structured diagnostic lenses (process, data, systems) to move from visible symptoms to root causes.
• Data reality bounds AI ambition: What AI can reliably do is determined by the strength of the data foundation (architecture, integration, quality, consumption) not by model choice.
• Not all AI systems are created equal: Machine learning, LLMs, and agents introduce different capabilities, constraints, and operational trade-offs. Enterprise-ready agents specifically require probabilistic reasoning balanced with deterministic rules, structure, guardrails, and human oversight.
• Risk is predictable: Enterprise AI risk falls into defined categories: data privacy, bias, explainability, and governance. Principles define what good looks like; governance establishes ownership, decision rights, and escalation.
• Execution credibility matters as much as technical ambition: “Crawl”and MVP solutions that are in production beat “Run” enterprise-wide solutions that aren't.

RESPONSIBILITIES

What you own

Client strategy and delivery

• Lead end-to-end engagement execution from strategy and diagnostic through deployment and commercial expansion
• Run executive discovery sessions translating ambiguous business problems into structured AI investment rationales
• Build the business case with the rigor of an investor, not the optimism of a vendor: quantified value, honest constraints, sequenced roadmap
• Own the relationship with C-suite and senior client stakeholders as a peer, not a service provider

Technical leadership

• Apply working fluency in LLMs, agentic workflows, RAG architecture, and data infrastructure to make real design decisions ensuring the original business value is obtained
• Collaborate with engineering to challenge, refine, and pressure-test solutions against production realities
• Define AI product roadmaps that are incrementally value generating, governed, measured, and adopted

Firm development

• Identify capability and offering gaps where Quantum Rise can build durable competitive advantage
• Build reusable delivery IP (frameworks, playbooks, diagnostic tools) that improve every engagement that follows
• Develop and mentor the next generation of AI consultants on what it means to operate at the intersection of AI strategy and delivery
• Contribute to business development through the quality of your work and the depth of your client relationships

THE PROFILE

Who fits here

person who thrives in this role has a particular combination that's genuinely rare and we'd rather name it honestly than let both sides waste time discovering the mismatch.

Dimension: What this looks like in practice

Role identity: You think of yourself as a strategist who builds things, not a consultant who advises on them.

Technical depth: Hands-on with LLMs and agentic coding. You've debugged a pipeline at some point and don't need to be reminded why hallucination is an enterprise risk.

Business fluency: You can translate AI capability into a CFO-ready investment case without losing the technical precision that makes it credible.

Delivery record: 12+ years in management consulting or technical advisory with real end-to-end accountability from scoping through go-live. You are hyper customer service oriented.

Sector context: You have meaningfully operated across 3 discrete sectors learning to how effectively understand how money is actually made, customer and demand dynamics, how work gets done, regulatory constraints, etc.

Education: Engineering, CS, or MIS undergraduate foundation. MBA preferred. The combination matters and what makes the translation instinct natural. What matters is the ability to translate value creation into technology and vice versa.

Working style: You reach for the AI tool first because it's genuinely how you think and not just because we’re an AI consultancy.

BENEFITS

What we offer

• Competitive base salary + variable compensation tied to individual and company performance
• Equity options
• BCBS health, vision, and dental
• 401(k) with discretionary annual match
• FSA, DCA, commuter, and L&D stipends
• Unlimited PTO + paid holidays + paid sick time