Manager

We are seeking highly skilled GenAI Application Leads with 8 to 15 years of total experience to lead the design, development, testing, and deployment of Generative AI–based applications focused on Data and Analytics within the Life Sciences domain.

• AI Engineering
• Data Analytics
• Full-stack Development

Your goal will be to create intelligent applications that augment data-driven decision-making for our global clients.

Solution Architecture & Design

• Lead end-to-end architecture and design of Generative AI applications combining LLMs, RAG, Knowledge Graphs, and multi-agent systems.
• Define solution blueprints for structured/unstructured data sources and translate business requirements into modular AI workflows ensuring scalability and security.
• Evaluate GenAI frameworks (LangChain, LangGraph, Semantic Kernel) and design semantic data models with pharma domain experts.

Gen AI Application Development & Engineering

• Lead full-stack development using Python (FastAPI/Flask), React, or Next.js for GenAI-powered frontends.
• Build secure microservices/API layers and ensure robust CI/CD pipelines with Docker/Kubernetes containerization.
• Create user-centric applications embedding AI outputs into custom UIs or enterprise BI tools like Power BI.

Digital Workforce & Data Integration

• Connect GenAI apps to existing ecosystems (AWS S3, Azure Data Lake, Snowflake, Databricks) using knowledge graphs and metadata-driven approaches.
• Azure OpenAI/AWS SageMaker/Bedrock experience required for deploying AI workloads.

Model Integration & Fine-tuning

• Integrate LLMs (OpenAI, Anthropic Claude, Mistral) into enterprise applications and fine-tune models using domain-specific Life Sciences data (commercial, clinical, market access).
• Implement RAG architectures with vector databases (ChromaDB, Pinecone, FAISS) to enhance contextual reasoning.

Lifescience Leadership & Collaboration

• Lead cross-functional teams of engineers, data scientists, and UI developers.


• Spearhead knowledge-sharing sessions and PoCs to evangelize Generative AI adoption.
• Contribute to roadmaps relevant to GenAI in Life Sciences. Education: BE/B.Tech or Master's degree required.