Advisor - ML Engineering & Operations

ML Architecture & Pipeline Design: Own end-to-end machine learning architecture, feature engineering, and automated pipeline design decisions across key commercial analytics initiatives, establishing architectural patterns and design standards for broader engineering teams.

Agentic AI & LLMOps Implementation: Architect and deploy production-grade agentic AI systems utilizing LangGraph for multi-step reasoning, tool orchestration, and complex workflows. Own the LLMOps practice, including prompt versioning, evaluation frameworks, cost/latency monitoring, guardrails, and RAG architectures integrated with vector databases like Pinecone.

CI/CD & MLOps Infrastructure: Drive CI/CD orchestration, automated testing, and containerized deployment across multi-project environments using Docker, Kubernetes, Prefect, MLflow, Kedro, and GitHub Actions.

Cross-Functional Leadership & Integration: Function as the primary technical point of contact with Eli Lilly's Agentic AI engineering team, defining technical contracts, APIs, and shared SLAs. Provide technical mentorship, architectural code reviews, and problem-solving support for 2-3 junior engineers.

Core ML & Data Engineering: Advanced mastery of Python, PySpark, core ML frameworks (PyTorch, TensorFlow, scikit-learn, Keras), and working knowledge of R for Data Science pipeline hand-offs.

Cloud & Orchestration: Proficient with AWS SageMaker, AWS Lambda, serverless services, LangGraph, vector databases (Pinecone), Docker, Kubernetes, Prefect, and MLOps platforms.

Technical Mentorship: Lead informal technical oversight for junior machine learning engineers, driving code quality and architectural integrity without formal line-management responsibilities.

Commercial Analytics Transformation: Connect advanced generative AI capabilities with commercial decision-making across Eli Lilly's global marketing, sales, and medical affairs functions.

Workplace Culture: Collaborative analytics hub in Bengaluru operating alongside Indianapolis HQ teams.

Total Rewards: Exceptional salary package, performance bonuses, health benefits, disability support, and access to advanced enterprise AI technologies.