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Propy is revolutionizing the real estate industry by building the world's first AI-powered Title and Escrow platform onchain. We have processed over $5B in transactions, and we are on a mission to make closing on a home as easy as buying a stock.

We combine blockchain for security with advanced AI to automate the heavy lifting of closing documents. We aren't just "using" AI; we are building the infrastructure that allows AI agents to securely manage escrow, eliminate fraud, and run 24/7.

We are looking for a pragmatic Applied AI Engineer to join our engineering team.

The role is not about training models and does not involve academic Machine Learning research. It is about building the rails that make AI usable in a high-stakes financial environment. You will bridge the gap between our robust C#/.NET architecture and the probabilistic world of LLMs.

Title and Escrow is a document-heavy industry with zero room for error. Your mission is to use AI to clean up the messiness of real-world real estate data.

You will solve problems like:

• Structured Data Extraction: Converting messy, unstructured data (like emails, PDFs, documents)  from various sources into strictly validated JSON schemas with as close to 100% accuracy as possible.
• Escrow Automation: Designing workflows that reduce human intervention by 50% by intelligently routing tasks based on AI analysis.
• Fraud Detection: Implementing deterministic logic checks on bank and financial documents to detect fraud patterns before they happen.

• Engineer the Integration: Writing production-grade code that interacts with external AI APIs
• "Prompt Engineering" as Code: You won't just write prompts; you will version, test, and optimize them. You will define strict schemas to ensure the AI speaks the language of our internal tools.
• Orchestrate & Validate: Help in building the logic that parses AI responses, validates them against our database (MongoDB), and flags inconsistencies before they reach the user.
• Full-Stack Implementation: Work to visualize AI-aided services and data for user review and approval.
• Collaborate: Work closely with the other senior engineers and product owners to translate complex "Title & Escrow" schemas into technical constraints that an AI can understand.

• Developer DNA: You are a software engineer first. You have strong experience in Python (C# / .NET is an advantage) and understand programming in depth. 
• Applied AI Experience: You have integrated LLMs into applications via API. Have experience with not only models but also AI frameworks. Experience with workflows, AI agent building and orchestration. You understand context windows, token limits, temperature, and guardrails.
• Data Handling: Experience with handling complex data structures.
• The "Glue" Mindset: You enjoy writing the code that connects different services ( like the AWS, AI APIs, and Database) to make a seamless features.
• Collaborative Autonomy: You will own the AI domain, but you won't be on an island. You will be embedded in a senior engineering team that supports you with architecture, code reviews, and best practices.

• Experience with AWS infrastructure.
• Familiarity with the US Real Estate, Title, or Escrow process.

• Working in a transparent environment which focuses on solving problems and getting things done.
• The opportunity to work with very smart and driven people.
• The ability to grow your talents and career in a high-growth sector.
• A remuneration package that is based on the candidate's motivation, skills, and experience.

Please submit your resume to this job ad along with a portfolio of your AI-related experience, GitHub account and anything else you find applicable. 

Job description:-

Position: Gen AI Engineer

Location: Irving TX

Duration: 12+ months

Job Overview

In this role, you will be responsible for translating AI strategy into tangible, production-ready capabilities that enhance operational efficiencies and drive business value. We're looking for someone who combines deep technical expertise in generative AI with a proven track record of successfully delivering complex technology projects.

Required Technical Skills

Deep knowledge of LLMs and advanced fine-tuning techniques. Proficient in Parameter-Efficient Fine-Tuning (PEFT) methods (LoRA, QLoRA, Adapter Tuning, Prefix Tuning), full fine-tuning, instruction tuning, and agentic AI techniques (RLHF, multi-task learning).

Expertise in model compression and quantization methods (AWQ, GPTQ, GPTQ-for-LLaMA). Proficiency with optimized inference engines such as vLLM, DeepSpeed, and FP6-LLM.

Adept at advanced prompt engineering techniques and best practices. Familiarity with frameworks that facilitate effective prompt design and management.

Advanced knowledge of RAG techniques, including hybrid search, multi-vector retrieval, Hypothetical Document Embeddings (HyDE), self-querying, query expansion, re-ranking, and relevance filtering.

Proficiency in TensorFlow, PyTorch, and Keras. Knowledge of distributed training, parallel processing, and extensive hands-on experience with AWS services for AI/ML.

Advanced NLP skills (NER, Dependency Parsing, Text Classification, Topic Modeling). Experience with Transfer Learning, Few-shot, and Zero-shot learning. Expertise in containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for MLOps.

Strong proficiency in data preprocessing, feature engineering, and handling large-scale datasets. Experience with real-time AI applications, streaming data, and designing RESTful APIs for model integration.

Experienced with LangGraph, Autogen, , LangChain, LlamaIndex, and Hugging Face Transformers. Familiarity with Gen AI APIs (OpenAI, Gemini, Claude) and version control systems like Git.

Knowledge of AI compliance frameworks and best practices. Experience implementing guardrails to ensure ethical AI usage and mitigate risks (e.g., Microsoft's AI Guidance Framework).

Dexian is a leading provider of staffing, IT, and workforce solutions with over 12,000 employees and 70 locations worldwide. As one of the largest IT staffing companies and the 2nd largest minority-owned staffing company in the U.S., Dexian was formed in 2023 through the merger of DISYS and Signature Consultants. Combining the best elements of its core companies, Dexian's platform connects talent, technology, and organizations to produce game-changing results that help everyone achieve their ambitions and goals.

Dexian's brands include Dexian DISYS, Dexian Signature Consultants, Dexian Government Solutions, Dexian Talent Development and Dexian IT Solutions. Visit to learn more.

Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

Note: Dexian Canada will, on request, provide accommodations for disabilities to support your participation in all aspects of our Recruitment and Assessment/Selection Processes.

** 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

Voxology is redefining patient engagement with AI-driven solutions designed to streamline healthcare access and administrative processes. Our mission is to enable healthcare providers to deliver effortless, patient-centric experiences.

Through advanced conversational AI, we power seamless communication across voice, text, and chat—reducing wait times, improving access, and enhancing the overall patient experience. By integrating with leading EMRs, we simplify the end-to-end patient journey, from scheduling and intake to financial clearance and follow-up, allowing providers to focus on delivering exceptional care.

We’re looking for a healthcare front office professional to help improve the quality and accuracy of AI-driven patient interactions.

This is a part-time (5–10 hrs/week), remote role where you’ll review real patient calls, identify issues, and help refine how AI agents handle scheduling, intake, and patient communication.

If you’ve worked at a front desk, call center, or in patient access, this is a great opportunity to get exposure to AI while leveraging your real-world experience.

• Listen to recorded patient calls and review transcripts
• Identify issues in conversations (missed scheduling opportunities, incorrect responses, confusing workflows)
• Provide clear, actionable feedback on what should have happened instead
• Tag and label conversations (patient intent, outcomes, error types)
• Ensure AI workflows align with real-world front office processes
• Identify patterns and recurring issues across interactions

• 1+ year experience in a healthcare front office role, such as:
• Patient Access Representative
• Medical Receptionist
• Scheduling Coordinator
• Healthcare Call Center Agent
• Strong attention to detail
• Comfortable reviewing calls/transcripts and providing structured feedback
• Understand how real patient conversations and workflows operate

• Experience with EMRs (Athena, NextGen, Epic, etc.)
• Exposure to scheduling, insurance verification, or referral workflows
• Prior QA, auditing, or call review experience

• Work on real-world AI used by healthcare providers
• Directly impact patient experience and access to care
• Flexible, part-time schedule
• Strong entry point into healthcare + AI

• Location: Remote
• Time Commitment: 5–10 hours per week
• Compensation: $20–$40/hour (based on experience)

Role:

Join project teams across the U.S. as the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Location: New Haven, Connecticut

Responsibilities:

• Opportunity hunting and workflow redesign – Lead Lean/Six Sigma discovery workshops; map value streams, assess process and data maturity, and log low-effort/high-impact AI use cases.
• Process and data maturity assessment – Evaluate each jobsite’s current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents.
• Assess the market solutions – Evaluate off-the-shelf and platform tools; launch pilots, measure impact, and scale wins.
• Rapid AI-agent builds – Convert user stories into production-ready agents in Copilot Studio / Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks within days; wire them to Teams/SharePoint on the front end and Databricks Lakehouse or other sources on the back end.
• Enterprise-grade engineering & LLMOps – Build RAG pipelines backed by Delta tables, Unity Catalog, and Databricks Vector Search; automate infra with GitHub Actions / Posit; monitor latency, cost, adoption, and drift.
• Data integrations – Partner with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents.
• Cross-cloud orchestration – Blend OpenAI, Azure OpenAI, and AWS Bedrock behind secure custom connectors; package agents for seamless rollout.
• Change enablement – Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs, and track behavior change KPIs.
• Stakeholder communication – Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for “Construction Site of the Future.”
• Escalation & hand-off – Draft clear user stories, data specs, and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering / Data Science team to lean in.

Qualifications:

• 3+ years in AI engineering / full-stack data applications or data science, including 2+ years building production LLM/RAG solutions.
• Bachelor’s in CS, Engineering, Physics, or a related field; Master’s preferred.
• Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Demonstrated process excellence background (Lean/Six Sigma Green Belt or equivalent) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence.
• Strong facilitation and communication skills.
• Hands-on expertise with Copilot Studio, Power Apps/Automate, custom connectors, and CoE Toolkit governance.
• Programming & data stack: Python, SQL, Databricks Lakehouse, vector stores.
• DevOps & IaC: GitHub Actions (or Azure DevOps) and Posit Workbench/Connect automation or comparable CI/CD tooling; strong Git/GitHub workflow discipline.
• Integration & ETL skills: Foundational understanding of ETL/ELT design, Airflow or Databricks Workflows, and REST/GraphQL API development; proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines.
• Willing and able to travel and work on active jobsites.

Must be local to TX

Role Overview

• He’s ideally looking for someone with 13+ years of experience, strong architecture depth, and the ability to clearly explain designs.
• Must have experience using AI is used in day‑to‑day development.
• Must have experience as a API Developer to lead the development and deployment of our backend services. In this role, you will be the bridge between our PostgreSQL database and React frontend, responsible not only for writing high-performance Python code but also for architecting the CI/CD pipelines that bring our applications to life. You will ensure our integration layers are scalable, secure, and automatically deployed.

Job Summary

We are seeking a Principal-level Full Stack Lead Developer with 13+ years of experience to drive high-priority engineering workstreams. This role is for a technical heavyweight who can lead new projects in parallel with existing leadership while maintaining exceptional architecture depth. You will be responsible for the full lifecycle of high-performance FastAPI and React applications, ensuring they are resilient, observable, and scalable. We expect a leader who views AI development tools as a force multiplier for velocity and can clearly articulate complex design decisions to stakeholders.

Key Responsibilities

• Project Sovereignty: Independently lead and deliver new, complex workstreams from inception to launch, acting as a technical peer to existing leadership (e.g., Sai).
• System Architecture: Design and defend distributed microservices and event-driven architectures. You must be able to clearly whiteboard and communicate design patterns to both technical and non-technical audiences.
• Hands-on Execution: Maintain high-velocity output of clean, production-grade code using FastAPI (Python) and React (TypeScript).
• Platform Reliability: Architect and implement global Error Handling frameworks, centralized Logging (e.g., OpenTelemetry, ELK), and API Management strategies including Rate Limiting and versioning.
• Event-Driven Messaging: Oversee the implementation of asynchronous service communication using ActiveMQ or AWS EventBridge.
• AI-Augmented SDLC: Deeply integrate AI coding tools (e.g., CloudCode, Cursor, GitHub Copilot) into daily workflows to accelerate prototyping, refactoring, and automated testing.
• Engineering Mentorship: Foster a culture of excellence through rigorous code reviews and by unblocking senior engineers on complex technical hurdles.
• Product Collaboration: Work closely with Product Managers to turn high-level roadmaps into technical reality, providing accurate estimates and identifying technical risks early.

Required Skills & Qualifications

• Experience:13+ years of professional software development with a proven track record of leading large-scale products.
• Tech Stack Mastery: Expert-level FastAPI (Async Python) and modern React (Hooks, TypeScript, Performance Profiling).
• Advanced Governance: Hands-on experience with API Gateway patterns, request throttling, and securing distributed systems (OAuth2/JWT).
• Observability & Messaging: Deep knowledge of structured logging, distributed tracing, and message brokers (ActiveMQ or EventBridge).
• AI Tooling: Advanced proficiency in using AI tools for Fast Development to reduce manual overhead and multiply team output.
• Database & Infrastructure: Expert-level PostgreSQL (tuning/indexing), Redis (for caching/rate-limiting), and container orchestration (Kubernetes/Docker).
• Communication: Exceptional ability to translate technical "scars" and architectural risks into clear business impact.

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.

• 
  
• 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.
  

Looking for a 10+ years of experience in full stack software development, including front-end, back-end, and database technologies in Bothell, WA and its an onsite role.

• Bachelor’s degree in computer science, software engineering, or a related field preferred
• Proficiency in modern programming languages and frameworks such as Python, JavaScript, Java, Next JS, Node.js, React js
• Strong working experience with GenAI, LLM Models, MCP, Vector DB, RAG, Vertex AI, Agentic AI frameworks like NGA, ADK or LangChain/LangGraph, creating AI agents.
• Strong experience with Cloud platforms like GCP, Azure or AWS and cloud technologies like OpenStack, Terraform, Ansible or Chef
• Experience working with LLM observability, analytics, evaluations, testing and annotation using tools like LangSmith, LangFuse, Streamlit, Arize or similar tools.
• Strong experience working with AI/ML development
• Strong experience working with Databases like Cassandra, MongoDB or similar.
• Strong understanding and working experience of microservices architecture, RESTful APIs, Caching and related technologies
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes
• Proficiency in version control systems like Git, and experience with CI/CD tools such as Jenkins, GitHub, Maven, Nexus, JFrog or Sonar
• Strong experience in Unit and Function testing using Junit, Mockito/JMock, Selenium, Robot, Cucumber, SoapUI or Postman
• Strong problem-solving, analytical, and debugging skills.
• Excellent written and verbal communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
• Demonstrated experience in mentoring and providing technical leadership to other engineers.

• Nice to have skills:
• Google CCAI platform (DialogFlow), Vertex AI, Graph QL, BigQuery, Conversation Graph, LLM as Judge

About This Role

This isn't a traditional engineering role where you'll receive detailed specifications and build to order. We're looking for someone who digs into problems firsthand—someone who asks "why" until they truly understand what's broken, then builds the solution themselves.

If you've ever been frustrated by the gap between people who understand the customer and people who can build technology, this role exists because we share that frustration. We want someone who can do both.

What You'll Do

You'll use AI tools—particularly Claude Code and the Claude platform—to build solutions that solve real problems in mortgage lending. Not proofs of concept. Real tools that people use every day.

Examples of problems you might tackle:

• Loan conditions arrive from Fannie Mae, Freddie Mac, VA, and FHA in different formats. Loan officers spend hours reconciling them. Build something that consolidates and deduplicates them automatically.
• Underwriters spend significant time on tasks that could be automated, but "that's how it's always been done." Identify which tasks, understand why, and build the automation.
• Compliance requirements evolve constantly. Build systems that can adapt without requiring lengthy development cycles.

You won't always be handed a clear spec. You'll often be handed a problem—sometimes a vague one—and expected to dig in until you understand it well enough to solve it.

What We're Looking For

Required:

• You can build working software. You don't need a team of engineers to ship something useful. Claude Code, Python, JavaScript, APIs—you're comfortable getting hands-on.
• You go deep on problems. When someone says "we need a dashboard," you ask what decision they're trying to make. When they say "it takes too long," you ask how long, why, and what happens as a result.
• You're persistent. You don't hear "that's not possible" and stop there. You get curious and look for another way.
• You communicate well across audiences. Executives, loan officers, underwriters, compliance teams—you can work with all of them effectively.

Preferred:

• Bachelor's degree in Business, Computer Science, or related field
• Experience in mortgage lending, financial services, or another regulated industry
• Hands-on experience with AI coding tools (Claude Code, Copilot, Cursor, or similar)
• Background that spans both business and technical work—perhaps you started in analysis and taught yourself to code, or you're an engineer who consistently finds yourself thinking about the customer problem

What matters most:

We care less about your pedigree and more about your ability to solve problems and work well with others while doing it.

Why This Role Exists

We're a 200-person mortgage lending organization, and we believe AI is going to fundamentally change how our industry operates—not by replacing people, but by making our people dramatically more effective.

We're moving away from the traditional model where business teams write requirements, hand them to engineers, and hope the result matches the intent. We want to build a team of people who can understand the problem deeply and build the solution directly. Fewer handoffs. Faster iteration. Better outcomes.

If that resonates with you, we'd like to talk.

How To Apply

Please send:

1. Your resume
2. Something you've built — a link, screenshot, GitHub repo, or brief walkthrough. It doesn't need to be polished. We want to see how you approach problems.
3. A short note (a few sentences) about a problem you investigated deeply and what you learned from it