AI/ML Engineer

Overview

The AI Subject Matter Expert (SME) will provide hands-on leadership across technical delivery and strategic advisory initiatives, ensuring successful implementation of enterprise AI and GenAI solutions while supporting multiple teams and programs.

Must-Haves

• Production Agentic System / LLM Pipeline Experience
• Has actually shipped a multi-phase LangGraph (or equivalent) agentic workflow.
• Experience with retries, branching, evaluations, and observability.
• Beyond notebook prototypes and proof-of-concepts.
• RAG at Scale
• Comfortable with chunking strategies.
• Embedding model selection experience.
• Understanding of vector store trade-offs (Azure AI Search, pgvector, etc.).
• Experience with structured extraction from PDFs, Word documents, and HTML content.
• Cloud-Native on Azure
• Experience with:
  • Azure OpenAI
  • Azure Functions / Container Apps
  • ADLS
  • Cosmos DB
  • Key Vault
  • Application Insights
• Bonus: Experience with GCP / Vertex AI.
• Python Skills
• Strong working knowledge of Python.
• Ability to build, debug, and maintain production services.
• Pragmatic About Evaluations
• Ability to establish evaluation harnesses for LLM pipelines.
• Understanding of:
  • LLM-as-judge approaches
  • Deterministic checks
  • Human review processes
• Agent Hardening Experience
• Prompt injection defense.
• Tool-use safety.
• Sandboxing.
• Understanding of failure modes in agentic systems beyond traditional RAG implementations.
• MCP / Tool-Calling Fluency
• Familiarity with MCP servers.
• Function-calling patterns.
• Understanding of Claude, OpenAI, and Gemini tool conventions.
• Clear Written Communication
• Produces high-quality design documents, ADRs, and review comments.
• Able to communicate effectively with technical and senior leadership audiences.

Nice-to-Haves

• Life Sciences / Regulated Industry Context
• Understanding of:
  • IHD
  • GxP
  • Consent scope
  • Audit trail requirements
• Familiarity with Governance-as-Code Concepts
• Knowledge of:
  • Data classification
  • Data lineage
  • FAIR principles
• Frontend Competence for Internal Tools
  • Streamlit
  • Gradio
  • React
• Ability to create simple interfaces that help make concepts concrete.
• Previous Technical Leadership Experience
  • Has served as a Tech Lead, even on a small team.
  • Experience balancing engineering decisions and delivery.
• Additional Expectations
  • Profile should be sufficiently hands-on and capable of operating across both technical delivery and strategic advisory activities.
  • Should not be purely innovation or consulting focused.
• Enterprise GenAI / LLM implementation experience is highly valuable.
• Ability to provide architecture guidance.
• Ability to support multiple initiatives and teams in parallel.

Related Knowledge Areas

• Data Quality Governance
• Information Architecture (DKC)
• Data Quality
• Data Lineage
• AI Data Stewardship
• Product Backbone
• Governance Portal
• Metadata Management
• Catalog
• Semantic Data Ontologies
• Master Data
• Knowledge Areas
• Governance
• Information Architecture
• Lineage
• Quality
• FAIR Principles
• Regulatory and Industry Data Standards
• Business Context
• Processes
• Key Data Flows
• Translating Business Needs into Trusted Data Products