Senior AI/ML Engineer

Summary

Join Detroit Labs as a Senior AI/ML Engineer for a 12-week (potentially extendable) contract position. You will serve as the AI Lead on a project focused on transforming reactive risk management into real-time strategic foresight using predictive AI. This role involves architecting, developing, and deploying intelligent agent systems powered by large language models. You will leverage your full-stack expertise in Python (FastAPI), TypeScript (React/Next.js), and cloud platforms (AWS, GCP). The position offers an hourly rate of $120/hr and is remote-friendly. The ideal candidate will have extensive experience with LLMs, generative AI, and prompt engineering.

Requirements

• 10+ years of experience in full stack software engineering, preferably with production SaaS platforms
• Advanced proficiency in Python (FastAPI); frontend development in TypeScript/React/Next.js; deep experience with Azure Cloud
• Extensive hands-on experience with LLMs and generative AI—building, deploying, and optimizing applications through APIs and open-source frameworks (OpenAI, Hugging Face, LangChain, LangGraph)
• Expertise in MCP concepts including prompt structures, shared model state, and protocol-driven agent interactions
• Deep fluency in prompt engineering, agent tool integration, chaining, and decomposition of LLM tasks for scalable use
• Experience with multi-agent orchestration and deployment on scalable infrastructure
• Knowledge of CI/CD for rapid SaaS releases; commitment to code quality, maintainability, and documentation
• Strong communication skills for technical and non-technical audiences

Responsibilities

• Architect, implement, and maintain full stack AI applications using modern backend (Python, FastAPI), frontend (TypeScript, Next.js or React), and cloud platforms (GCP, AWS)
• Develop and deploy LLM-powered agent systems including planning, memory, tool usage, and user interaction flows
• Design, develop, and integrate Model Context Protocol (MCP)-compliant servers for structured, context-rich interactions between LLM agents and models
• Build and maintain APIs, agent orchestration frameworks (e.g., AutoGen, CrewAI, LangGraph), and robust multi-agent coordination pipelines
• Lead all aspects of prompt engineering: generation, optimization, chaining, context/rag, and dynamic deconstruction for LLM workflows
• Integrate and manage vector and semantic databases (e.g., Qdrant) for persistent agent memory, context retrieval, and semantic search
• Collaborate with cross-functional teams to launch intelligent user-facing tools and ensure fast, reliable, and scalable SaaS delivery
• Drive best practices for observability, debugging, and LLM evaluation, including test harnesses and human-in-the-loop review
• Understanding of data privacy, AI ethics, and model governance for enterprise deployments
• Mentor junior engineers, champion full stack and AI/ML culture, and stay abreast of AI research and SaaS platform trends

Benefits

• Compensation for this role is on an hourly basis and is $120/hr
• Equipment to complete your work
• Remote friendly position