Principal Product AI Data Engineer
Clarivate (company site, opens in a new tab)10+ yrsBengaluruHybridDirect career pageEst. 40–65 LPA
Posted on 1 Sept
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Clarivate
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Clarivate you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design, architecture, and delivery of scalable Generative and Agentic AI systems and workflows for Life Sciences and Healthcare products.
- Collaborate cross-functionally with product, engineering, analytics, and business stakeholders to build AI-enabled data products aligned to strategic priorities.
- Establish engineering standards, mentor engineers, and drive AI initiatives including MLOps, model productionization, and integration of Generative AI/LLMs into enterprise applications.
Minimum Requirements
- Bachelor’s Degree or equivalent in Computer Science, Software Engineering, Artificial Intelligence, or related field.
- 10+ years of experience building and delivering production-grade software with AI-powered product capabilities.
- Strong proficiency in Python, PySpark, SQL, Snowflake, Databricks, Airflow, Delta Lake, and cloud platforms (AWS or Azure).
- Work Experience Required: 10+ years; Location: Bangalore with hybrid work model.
Ideal Candidate Profile
- Experience in leading complex AI system architectures and delivering end-to-end AI/ML engineering solutions in regulated Life Sciences or Healthcare domains.
- Demonstrated ability to partner effectively with product managers, business analysts, and executive leadership to drive measurable business outcomes.
- Hands-on expertise in MLOps, scalable feature engineering pipelines, and integrating advanced AI technologies like Generative AI and vector databases into production environments.