Position Summary:
Responsibilities:
- Solution Architecture & Design
- Define solution blueprints combining LLMs, Retrieval-Augmented Generation (RAG), Knowledge Graphs for structured and unstructured data sources.:
- Translate business requirements 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.
- Gen AI Application Development & Engineering
- Lead full-stack design and development using Python (FastAPI, Flask) and React/Next.js for GenAI-powered frontends.
- 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).
- 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
- 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
- Lead a cross-functional GenAI development team of engineers, business analysts, data scientists, and UI developers.
- Stay ahead of the curve with emerging LLM architectu

📌 Senior Manager (C)
🏢 Axtria
📍 C