Lead AI Engineer – Agentic AI | Pharma Domain

Experience: 6–9 Years

Location: Bengaluru

Work Mode: Hybrid | 4–5 Days

CTC: ₹22–36 LPA

Joining: Immediate / Within 1 Week

About the Role

We are looking for a Lead AI Engineer with strong experience in Agentic AI, Generative AI, LLMs, RAG, and AI system architecture to build and deploy production-grade AI solutions for the Pharmaceutical and Life Sciences domain.

The ideal candidate should have hands-on experience building multi-agent systems, RAG pipelines, tool orchestration, AI integrations, and cloud-based production systems, along with experience working with regulated pharma data.

Key Responsibilities

- Design and develop agentic AI systems, including multi-agent workflows, tool orchestration, retrieval and memory systems.
- Build production-grade solutions using LangGraph, LangChain, AutoGen, CrewAI, or equivalent frameworks.
- Design and optimize RAG pipelines, including document ingestion, chunking, embeddings, vector search, hybrid retrieval and evaluation.
- Integrate AI systems with pharma data platforms and APIs such as IQVIA, Symphony Health, Komodo and Veeva.
- Build observability and evaluation frameworks to monitor latency, cost, quality and model performance.
- Own component-level architecture, including data flows, API contracts, failure handling and system design.
- Lead CI/CD, containerization and production deployment using Docker, Kubernetes and cloud platforms.
- Develop intelligent document processing solutions for clinical reports, drug labels, HEOR documents and regulatory content.
- Work on AI use cases involving medical affairs, commercial analytics, KOL mapping,



competitive intelligence and signal detection.
- Mentor AI engineers through code reviews, design discussions and technical problem-solving.
- Communicate technical architecture and trade-offs effectively with both technical and non-technical stakeholders.
- Ensure solutions follow appropriate GxP, HIPAA and 21 CFR Part 11 requirements.

Mandatory Skills & Experience

- 6+ years of software/ML engineering experience.
- At least 2+ years of hands-on experience building and deploying production LLM/Agentic AI systems in the pharma domain.
- Strong hands-on experience with at least 2 agentic AI frameworks, such as LangGraph, LangChain, AutoGen or CrewAI.
- Experience with Anthropic Claude API, OpenAI Assistants API or Vertex AI Agent Builder.
- Strong Python skills with production-quality coding, testing, packaging and performance optimization.
- Solid understanding of RAG pipelines, embeddings, vector databases, hybrid search and evaluation frameworks such as RAGAS.
- Experience with AWS, Azure or GCP, along with Docker, Kubernetes, Terraform/CDK and CI/CD.
- Experience with LangSmith, Helicone or equivalent observability platforms.
- Experience designing complete AI sub-systems involving agent topology, data flows, APIs, failure handling, retrieval and memory.




- Proven track record of deploying 2+ AI/ML or agentic systems into production.
- Working knowledge of pharma commercial data, including Rx/claims, NPI-level analytics and brand performance metrics.
- Experience working with regulated data environments, including GxP, 21 CFR Part 11 or HIPAA-compliant environments.
- Exposure to at least one area such as Medical Affairs, RWE, Clinical Operations, HEOR/Market Access or Regulatory Intelligence.
- Strong technical communication and documentation skills.
- Immediate joiner or currently serving notice period, with ability to join within 1 week.

Good to Have

- Model Context Protocol (MCP)
- Veeva Vault, Medidata, IQVIA or Symphony Health
- Neo4j / Amazon Neptune
- RLHF, fine-tuning or model adaptation
- Consulting / client-facing delivery experience

Important: This is a Bengaluru-based hybrid role and requires candidates who can join within 1 week. Pharma/Life Sciences domain experience is mandatory. Pay: ₹2,200,000.00 - ₹3,600,000.00 per year

Application Question(s)

- Do you have 6+ yr of years of experience in Software Engineering / ML Engineering?
- Do you have 2+ years of production LLM/Agentic AI experience specifically in the Pharma/Life Sciences domain?
- Which cloud and deployment technologies have you used hands-on?
- Have you independently owned an AI subsystem design covering agent architecture, data flow, APIs, failure handling, retrieval and/or memory?
- Have you worked in a regulated environment involving GxP, 21 CFR Part 11, HIPAA or similar compliance requirements?

Work Location: In person

📌 Lead AI Engineer – Agentic AI | Pharma Domain (Bengaluru)
🏢 S Talent HUB
📍 Bengaluru