Position Summary
Highly skilled GenAI Application Leads with 5 to 9 years of total experience who has worked on development 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.
Job Responsibilities
- Gen AI Application Development & Engineering
- Build microservices or API layers that expose AI functionalities securely across teams and systems.
- Ensure robust CI/CD pipelines, version control (GitHub, Bitbucket, GitLab), and containerization (Docker, Kubernetes).
- Develop 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.)
- Use knowledge graphs and metadata-driven approaches to enhance contextual reasoning and data discovery
- Deploy AI workloads using Azure OpenAI, AWS Sagemaker, Bedrock, or Snowflake Cortex AI Services.
- AI Model Integration & Fine-tuning
- Lead 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).
- Support the design of 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.
- Collaboration
- 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.Tech
Master of Computer Application
Work Experience
Highly skilled GenAI Application Leads with 5 to 9 years of total experience who has worked on development 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.
Behavioural Competencies
Ownership
Teamwork & Leadership
Cultural Fit
Motivation to Learn and Grow
Technical Competencies
Problem Solving
Lifescience Knowledge
Communication
Amazon SageMaker
Amazon Redshift
Jupyter Notebook
Python
SQL
React
