AI CoE Engineer
Version 1 (company site, opens in a new tab)5–8 yrsBengaluruOn-siteDirect career pageEst. 20–40 LPA
Posted 3h ago
Reach people at Version 1
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 Version 1 you could write to:
- Recruiters & HR
- People in this function
- Work addresses
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
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
- Collaborate with business teams to translate challenges into scoped AI use cases and build proof-of-concept AI solutions leading to production deployment.
- Design end-to-end architecture for agentic and generative AI solutions, managing model selection, data integration, security, and cost considerations.
- Lead production engineering of AI applications and mentor CoE colleagues including interns, setting technical standards and contributing to governance.
Minimum Requirements
- 5 to 8 years of software or data engineering experience with recent hands-on AI work involving large language models.
- Proficient in software engineering using Python or similar languages with experience delivering working AI systems.
- Working knowledge of cloud platforms, preferably AWS, and familiarity with data and integration patterns.
- Experience designing AI solutions end-to-end including architecture trade-offs.
Ideal Candidate Profile
- Experienced in building AI systems with agentic workflows and retrieval-augmented generation techniques, demonstrating practical production impact.
- Comfortable working in fast-moving, startup-like environments with a hands-on approach to problem-solving and rapid prototyping.
- Skilled mentor and communicator capable of supporting technical and non-technical stakeholders and raising AI capabilities across teams.