Director

Axtria - Ingenious Insights

Dadri

On-site

INR 5,000,000 - 7,000,000

Full time

14 days+

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Job summary

Axtria - Ingenious Insights is seeking a highly experienced GenAI Application Leader to drive design, development, testing, and deployment of Generative AI–based data analytics solutions in Life Sciences. The role emphasizes Python, RAG, knowledge graphs, and cloud integration across AWS/Azure, with hands‑on tuning of multiple LLMs.

The candidate will lead cross‑functional teams to build scalable AI workflows, ensure security and performance, and guide enterprise UI integrations using modern

Qualifications

15+ years of experience in GenAI, data analytics, and enterprise AI.
Strong Python and cloud-based AI deployment expertise.
Proven track record with LLMs, RAG, and knowledge graphs.
Experience with LangChain/LangGraph and prompt engineering.
Ability to design semantic data models for pharma/biotech contexts.

Responsibilities

Lead end‑to‑end architecture of Generative AI apps.
Guide teams on LLM, RAG, and knowledge graphs use cases.
Collaborate with data engineers and domain experts for semantic models.
Drive full‑stack development using Python and React/Next.js.
Evaluate GenAI frameworks and secure scalable solutions.
Design AI workflows with modular, secure, performant architectures.
Oversee integration of LLMs (OpenAI GPT, Claude, Mistral, Cortex).
Mentor a cross‑functional GenAI team and drive PoCs.

Skills

Python

RAG

Knowledge graphs

LangChain

LangGraph

AWS/Azure

GPT/OpenAI

Anthropic Claude

Mistral

Snowflake Cortex

FastAPI

Flask

React/Next.js

Databricks

Snowflake

Power BI

Education

BE/B.Tech

Master of Computer Application

Tools

LangChain

LangGraph

Semantic Kernel

ChromaDB

Pinecone

FAISS

Weaviate

Job description

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.

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.Tech
Master 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