McLaren Strategic Solutions is looking for a Generative AI Developer to play a pivotal role in a high-visibility US Healthcare legacy platform modernization assessment.

You will design and deliver secure, enterprise-grade Generative AI solutions that :

- Accelerate analysis of large-scale legacy US healthcare codebases

- Automate architecture artifact creation

- Support comprehensive gap analysis

- Generate high-quality deliverables for the target-state architecture and phased migration roadmap

All GenAI activities will be executed strictly within the client's approved, permissioned AI ecosystem (e., Azure OpenAI or equivalent client-instance tools) with zero use of public LLMs or external tools containing client data.

Key Responsibilities :

- Design and implement GenAI-powered tools and RAG pipelines to rapidly analyze legacy US healthcare codebases, identify state-specific customizations, map dependencies, and catalog shared components

- Build advanced prompt frameworks, LLM agents, and multi-step workflows to generate:

- Current-state architecture views and diagrams

- Target-state multi-tenant, cloud-native architecture recommendations

- Detailed gap analysis matrices and prioritized remediation themes

- Phased migration roadmaps with risk registers and low-risk execution blueprints

- Develop Retrieval-Augmented Generation (RAG) systems over code repositories, architecture documents, integration specs, and operational runbooks

- Integrate GenAI outputs seamlessly with enterprise tools (Jira, Confluence, Lucidchart, Git, approved AI platforms)

- Create reusable GenAI components for code quality analysis, non-functional requirement validation (performance, scalability, security, multi-tenancy), and observability recommendations

- Collaborate daily with Principal Architect, Solution Architects, Data Architects, and Senior Business Analysts to validate and refine all GenAI-generated content for accuracy and relevance

- Support production of executive-level decision packs and client-ready execution blueprints

- Ensure full auditability, traceability, and compliance of every GenAI usage (data privacy, security, and regulatory standards)

Requirements :

Must-Have Qualifications & Experience :

- Strong Python development experience

- 4+ years of hands-on delivery of Generative AI and LLM-based production solutions

- Proven expertise in building RAG pipelines and LLM orchestration at scale

Strong experience with :

- LLMs: OpenAI, Azure OpenAI, Anthropic (Claude)

- Frameworks: LangChain (or LlamaIndex)

- Embeddings & Vector Databases (Pinecone, Chroma, Weaviate, FAISS, Azure AI Search)

- Advanced prompt engineering (Chain-of-Thought, ReAct, agents, few-shot)

- API integration and ML pipelines (FastAPI, REST)

Key Technical Skills :

- Core : Expert-level Python, LangChain, RAG architecture, Vector embeddings, Prompt engineering

- LLM Platforms : OpenAI GPT series, Azure OpenAI, Anthropic Claude

- Vector & Search : Chroma, Pinecone, FAISS, Azure Cognitive Search

- Integration : REST APIs, Git, Jira/Confluence APIs

- Additional : Docker, basic CI/CD, SQL for data retrieval, experience with code analysis tools

- Experience working in regulated environments (Healthcare domain preferred)

Nice-to-Have :

- Prior exposure to legacy system modernization or large-scale enterprise application assessments

- US Healthcare domain knowledge (payer/provider platforms, claims, or data modernization)

- Experience with cloud platforms (AWS, Azure, GCP) and modern data platforms (Databricks, Snowflake)