Technical Lead (Applied AI)

Responsibilities

• Technical Leadership & Architecture

  • Lead architecture, design, development, testing, and deployment of enterprise software solutions (applications, data, integration, AI agents, AI models)

  • Participate in strategy and roadmap discussions, architecture definition, and technology evaluations

  • Mentor engineers through design reviews, code reviews, and technical guidance

  • Quickly evaluate and adopt new tools, technologies, and platforms to build prototypes and proofs-of-concept

  • Drive adoption of AI solutions and collaborate with engineering teams, product leaders, and domain experts to deliver results

  • Software Engineering

    • Design, develop, and maintain scalable, production-grade enterprise applications using modern languages and frameworks (Python, Java, C#, JavaScript)

    • Define and enforce coding standards, best practices, and design patterns across the team

    • Build and maintain CI/CD pipelines, infrastructure-as-code, and cloud-deployed services (AWS, Azure)

    • Integrate enterprise systems via APIs, event-driven architectures, and messaging platforms

    • Identify and resolve performance bottlenecks, technical debt, and system reliability issues

    • Data & Analytics

      • Work with large, complex datasets and ensure data quality and integrity

      • Analyze data to generate insights that inform both model development and broader solution strategy

      • Collaborate with stakeholders to translate business problems into data-driven solutions

      • AI / Machine Learning Development

        • Design, develop, and train machine learning and deep learning models for healthcare and insurance use cases

        • Perform data modeling and feature engineering to support model development

        • Develop custom model metrics and approaches tailored to specific business problems

        • Ensure models are scalable, reliable, and integrated into production systems

        • Agentic AI Development

          • Design and develop LLM-powered workflows and agentic systems that help users complete complex tasks, retrieve information, reason over enterprise data, or interact with internal systems.

          • Integrate LLMs with tools, APIs, databases, documents, and enterprise platforms using patterns such as function calling, MCP, RAG, and structured tool use.

          • Architect orchestration patterns for planning, task decomposition, memory, context management, and human-in-the-loop review where appropriate.

          • Develop orchestration layers to manage agent planning, memory, task decomposition, and execution loops

          • Evaluate agentic systems for correctness, reliability, safety, observability, auditability, and harden them for production readiness.

          • Stay current with emerging AI frameworks and platforms, selecting tools pragmatically based on client needs.

Qualifications

• Experience

  • 6+ years of experience in software engineering designing and developing enterprise applications, data/analytics solutions, and/or integration solutions

  • 1+ years of providing technical leadership as Tech Lead, Lead Engineer, or Architect

  • 1+ years in developing AI agents and/or AI model development and training

  • Education

    • Bachelor's Degree in Computer Science, Software Development, Software Engineering, or Computer Engineering

    • (Optional) Master's Degree or Minor in AI/Machine Learning or Statistics

    • AI Engineering Skills (Two or More)

      • Agentic AI: building and integrating autonomous AI agents using LLM APIs and orchestration frameworks (e.g., Anthropic Claude, OpenAI GPT, LangChain, CrewAI, AutoGen, MCP)

      • Machine Learning & Deep Learning: developing and training models using standard ML/DL frameworks (e.g., TensorFlow, PyTorch, scikit-learn)

      • Data Engineering & Feature Engineering: building data pipelines, performing feature engineering, and ensuring data quality across large, complex datasets

      • Context Engineering: Agentic SQL retrieval, MCP integration, agentic tool use, as well as vector databases & RAG techniques implementing retrieval-augmented generation patterns using vector stores (e.g., Pinecone, Weaviate, pgvector, ChromaDB), .

      • LLM Prompt Engineering & Fine-Tuning: designing and evaluating effective prompts, system instructions, and fine-tuning strategies for production LLM applications

      • AI Evaluation & Production Readiness: defining evaluation methods, testing model behavior, monitoring performance, and addressing reliability, safety, explainability, and auditability concerns

      • What We're Looking For

        • You move fluidly between writing code and leading a room — equally comfortable in a design review as you are in a pull request

        • You have strong opinions about architecture and aren't afraid to share them, but you know when to listen and adapt

        • You take ownership seriously — on small teams, your decisions have real impact and you're energized by that, not intimidated

        • You're genuinely curious about AI, not just checking a box — you've experimented with agentic systems, LLMs, or ML tools on your own terms

        • You communicate clearly with both engineers and non-technical stakeholders, and can translate complexity without dumbing it down

Location

• Metro Detroit or North Carolina Research Triangle (Raleigh, Durham, Chapel Hill)

• Hybrid: flexibility to work remotely, but not fully remote

• Travel to X by 2 offices (Farmington Hills, MI) and client sites (within US) is required when requested

Work Environment and Culture

• Work alongside smart, collaborative people who continually challenge and invest in each other

• Partner with seasoned architects to solve hard problems and challenge assumptions

• Small teams mean real ownership, with growth and responsibilities driven purely by individual performance

• Everyone has a voice and is encouraged to shape the company by sharing their interests, ideas, and feedback

Compensation & Benefits

• Base salary $143K–$185K, depending on experience, plus profit sharing

• Annual raises and promotions based on performance

• 401(k) with employer match

• Comprehensive health, vision, dental, life, and disability insurance coverage, plus voluntary benefits and HSA with employer contribution

• Home Office Reimbursement, Health and Wellness Reimbursement, and Professional Dress Allowance

• Professional Self-Development Program

• Paid vacation, unlimited sick days (as needed), and holidays

• Company-sponsored social events and an employee recognition rewards program

Sound Like You?

We're not looking for someone who has done everything — we're looking for someone who is driven to. If you thrive in environments where you can move fast, go deep, and make a real difference for clients solving complex problems in healthcare and insurance, we'd love to hear from you.