Manager

Axtria - Ingenious Insights; Gurugram District; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

Axtria - Ingenious Insights in Gurugram is seeking a GenAI Application Lead with 8–15 years of total experience to design, develop, test, and deploy Generative AI–based data analytics solutions in Life Sciences. You will leverage Python, RAG, knowledge graphs, and LLM frameworks (LangChain, LangGraph) with cloud platforms AWS/Azure, and fine‑tune models for real business use.

You will drive end‑to‑end architecture, collaborate with data engineers and domain experts, and ensure secure, scalable,

Qualifications

• 8–15 years total GenAI/AI delivery experience in Life Sciences.
• Strong Python, ML/DL and data analytics background.
• Experience with cloud platforms (AWS/Azure) and LLM fine-tuning.

Responsibilities

• Solution Architecture & Design for GenAI applications.
• Lead end‑to‑end architecture and design of GenAI apps.
• Define blueprints using LLMs, RAG, and Knowledge Graphs.
• Translate requirements into modular AI workflows with scalability and security.
• Evaluate GenAI frameworks/tools (LangChain, LangGraph, Semantic Kernel).
• Collaborate with data engineers and pharma experts on semantic data models.
• Lead GenAI development using Python (FastAPI/Flask) and React/Next.js.
• Build microservices and API layers, ensure CI/CD and containers.
• Embed GenAI outputs into enterprise BI tools like Power BI.

Skills

Python

React

LLM frameworks

RAG

Knowledge graphs

AWS

Azure

Problem Solving

Communication

Education

BE/B.Tech

Master of Computer Application

Tools

LangChain

LangGraph

Semantic Kernel

Docker

Kubernetes

GitHub

Snowflake

Job description

Job Description:

Position Summary

Highly skilled GenAI Application Leads with 8 to 15 years of total experience who can lead 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.

Job Responsibilities

• Solution Architecture & Design
• Lead the end‑to‑end architecture and design of Generative AI applications
• 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).
• Design and 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).
• 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 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.
• Contribute to Gen AI use case roadmaps, thought leadership relevant to GenAI in Life Sciences.

Education

• BE/B.Tech
• Master of Computer Application

Work Experience

Highly skilled GenAI Application Leads with 8 to 15 years of total experience who can lead 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.

Behavioural Competencies

• Teamwork & Leadership
• Motivation to Learn and Grow
• Ownership
• Cultural Fit
• Talent Management

Technical Competencies

• Problem Solving
• Lifescience Knowledge
• Communication
• Project Management
• Capability Building / Thought Leadership
• AIML
• Python
• React
• Azure ML Studio
• AWS CodeBuild
• ML Data Science
• Snowflake