Position Summary
Highly skilled GenAI Application Leader with 15+ years of total experience
who can drive the design, development, testing, and deployment of Generative AI–based applications
focused on Data and Analytics in Life Sciences domain
. The ideal candidate will have a strong background in Python, RAG, knowledge graphs, Gen AI/LLM frameworks (LangChain, LangGraph), AWS/Azure cloud services with hands-on experience integrating and fine-tuning GPT, Anthropic Claude, Mistral, or Snowflake Cortex for real-world business use cases. Strong client problem-solving skills across life sciences data and analytics is a plus.This role bridges AI engineering, data analytics, and full-stack development, creating intelligent applications that augment data-driven decision-making.
Job Responsibilities
- Solution Architecture & Design
- Lead the end-to-end architecture and design of Generative AI applications
- Drive solution and architecture discussions with client teams using LLMs, Retrieval-Augmented Generation (RAG), Knowledge Graphs for structured and unstructured data sources.
- Understand business requirements and guide team to build the same into modular AI workflows, ensuring scalability, security, and performance.
- Evaluate and recommend GenAI frameworks/tools (LangChain, LangGraph, Semantic Kernel, etc.)
- Collaborate with data engineers and pharma domain experts to design semantic data models and context-aware knowledge base.
- Leading Gen AI Application Development & Engineering Teams
- Drive full-stack design and development using Python (FastAPI, Flask) and React/Next.js for GenAI-powered frontends.
- Drive teams building microservices or API layers that expose AI functionalities securely across teams and systems.
- Design user-centric applications that embed GenAI outputs seamlessly into custom UI or enterprise BI tools like Power BI
- Work with data engineering and analytics teams to connect GenAI apps to existing data ecosystems (AWS S3, Azure Data Lake, Snowflake, Databricks, etc.)
- Drive usage of knowledge graphs and metadata-driven approaches to enhance contextual reasoning and data discovery
- AI Model Integration & Fine-tuning
- Drive the integration of LLMs (OpenAI GPT, Anthropic Claude, Mistral, Snowflake Cortex, etc.) into enterprise-grade applications.
- Fine-tune or prompt-tune foundation models using domain-specific data (commercial, patient, Omni -channel, clinical, or market access data).
- Design and implement RAG architectures leveraging vector databases (ChromaDB, Pinecone, FAISS, Weaviate etc.).
- Develop prompt engineering frameworks and guardrails to ensure factuality, interpretability, and compliance.
- Establish evaluation pipelines for model performance, accuracy, latency, and hallucination detection.
- Leadership & Collaboration
- Drive Gen AI use cases which are relevant to BIM practice (focused on data management and analytics)
- Drive adoption of Gen AI use cases across BIM practice to drive speed and efficiency gains
- Lead a cross-functional GenAI development team of engineers, business analysts, data scientists, and UI developers.
- Stay ahead of the curve with emerging LLM architectures, multi-agent systems, and reasoning frameworks to provide technical guidance to the teams.
- Drive knowledge-sharing sessions and PoCs to evangelize Generative AI adoption across the organization.
Education
BE/B.TechMaster of Computer Application
Work Experience
Highly skilled GenAI Application Leader with 15+ years of total experience
who can drive the design, development, testing, and deployment of Generative AI–based applications
focused on Data and Analytics in Life Sciences domain
. The ideal candidate will have a strong background in Python, RAG, knowledge graphs, Gen AI/LLM frameworks (LangChain, LangGraph), AWS/Azure cloud services with hands-on experience integrating and fine-tuning GPT, Anthropic Claude, Mistral, or Snowflake Cortex for real-world business use cases. Strong client problem-solving skills across life sciences data and analytics is a plus.This role bridges AI engineering, data analytics, and full-stack development, creating intelligent applications that augment data-driven decision-making.
Behavioural Competencies
Attention to P&L ImpactTeamwork & LeadershipLifescience KnowledgeCultural FitProblem solvingTalent ManagementCapability Building / Thought LeadershipDelivery Management- BIM/ Cloud Info Management
Technical Competencies
AWS CodeBuildML Data ScienceAIMLDatabricksSnowflakeAzure ML StudioML OpsML engineeringReactPython
