Position Summary :

We are looking for an AI Architect to lead the design and delivery of AI-first commercial data platforms for life sciences clients. The solutions range from AI powered self-serve front end application development, agentic AI orchestration layers and scalable back-end data engineering/warehousing on cloud-based platforms (Databricks, Snowflake), hosted on AWS/Azure stacks. You will serve as the primary technical authority on client engagements defining architecture, governing AI usage, and mentoring delivery teams from pre-sales through production cutover.

Required Experience :

- 10-15 years in Data Engineering, with 5+ years in pharma/biotech.

- Proven track record on presales, solution design and solution defence.

- Ability to present architecture decisions and risk trade-offs to senior client leadership.

- Hands-on experience on Claude Code.

- Hands-on experience on Generative AI pipelines, vector databases, feature stores.

- Hands-on experience on Databricks, Snowflake, Azure/AWS.

Technical Skillset :

- Claude Code : prompt engineering, agentic pattern design, Git-controlled template versioning.

- AI/LLM : Experience integrating large language models (Claude, GPT, or equivalent) into data engineering workflows; agentic AI patterns (LangGraph, LangChain, or equivalent).

- Snowflake / Databricks.

- Python, Pyspark, SQL.

- Tools : Soda, Collibra, Unity, DQ, Airflow, Streamlit, Jenkins.

- ServiceNow integration for ops support workflows (preferred).

Qualification :

- Bachelors/Masters in Engineering, Computer Science, Data Science, or equivalent.

- Certified Claude Architect.

- Certifications in cloud/data platforms preferred.

Education :

- BE/B.Tech.

- Master of Computer Application.

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.

- Architecting.

- Client Expectation Management.

- Databricks.

- Python.