About the role
- Build and deploy LLM-powered AI agents (including voice agents) in production, designed for real-world use cases
- Own the end-to-end lifecycle of AI systems — from problem scoping and design to deployment, monitoring, and continuous iteration
- Design and optimize prompts, RAG pipelines, and evaluation frameworks to improve accuracy, latency, and reliability
- Work directly with customers and Implementation Managers (IMs) to understand workflows, solve real-world problems, and drive successful go-lives and iterations
- 1–3 years experience in backend / data / AI engineering
- Strong in Python + SQL
- Experience or exposure to LLMs, RAG, or prompt engineering
- High ownership, ability to work in ambiguity and ship fast
- Comfortable working with customers and cross-functional teams
- B.Tech, BE, or M.Tech in Computer Science or a related discipline, with 1–3 years of relevant experience
- Experience with production LLM systems / AI agents
- Familiarity with evaluation, agent tooling, or voice AI
- Experience with Databricks, MongoDB, or distributed systems
- Startup or customer-facing engineering experience
- Work on real production AI systems (not demos)
- End-to-end ownership and fast iteration cycles
- Direct impact on enterprise customers and business outcomes
Mode of Work - In-Office