Job Summary

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.

Responsibilities

- 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





What We're Looking For

- 1-3 years experience in backend / data / AI engineering
- Robust 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

Preferred Qualification

- B.Tech, BE, or M.Tech in Computer Science or a related discipline, with 1-3 years of relevant experience

Bonus

- 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Agent Engineer (Bengaluru)
🏢 Prodigal
📍 Bengaluru