Overview
Design, build and deploy autonomous AI agents, tool-calling systems and intelligent workflows that automate and transform enterprise IT operations, working with Senior AI Engineers, Product Managers and business stakeholders.
What you'll do
- Build, test and deploy autonomous AI agents and multi-agent workflows (e.g., using LangChain, LangGraph, AutoGen or CrewAI) to automate enterprise processes.
- Integrate LLMs with internal enterprise databases, APIs and tools via standard protocols (e.g., Model Context Protocol - MCP, OpenAPI, Function Calling).
- Apply AI-first development techniques, including advanced prompt engineering, RAG (Retrieval-Augmented Generation), agentic memory management and structured output parsing.
- Develop maintainable, high-quality code in Python/TypeScript using AI-augmented coding environments (e.g., Cursor, Cody, Claude) while ensuring outputs pass strict security and compliance standards.
- Implement evaluation frameworks (Evals) and observability metrics to monitor agent accuracy, hallucination rates, latency and tool-execution reliability in production.
- Debug and resolve agent loop failures, non-deterministic behaviors and tool-integration errors using structured troubleshooting and diagnostic tools.
- Contribute to automated CI/CD pipelines, unit testing for non-deterministic AI outputs, and secure guardrail mechanisms (e.g., input sanitization, rate limiting, human-in-the-loop approvals).
What you'll need
- Hands-on software engineering experience with strong proficiency in Python or JavaScript/TypeScript.
- Practical experience building applications with Large Language Models (LLMs), including function calling, structured outputs and Retrieval-Augmented Generation (RAG).
- Hands-on familiarity with agentic frameworks/patterns (e.g., LangGraph, LangChain, AutoGen, CrewAI, LlamaIndex) or building custom agent loops.
- Solid understanding of the Model Context Protocol (MCP), tool integration via REST APIs/GraphQL, and prompt engineering best practices.
- Experience using AI developer tools (e.g., Cursor, Claude, Cody) with an enthusiastic mindset toward experimental "vibe coding" and agentic workflows.
- Strong understanding of SDLC, Git, containerization (Docker), and foundational DevOps/DevSecOps practices.
- Strong problem-solving abilities and quantitative analytical skills; comfortable dealing with non-deterministic systems and iterative debugging.
- Excellent communication skills and a collaborative, action-oriented mindset.
- Demonstrated experience connecting AI models/agents with 3rd-party enterprise platforms or databases (e.g., Salesforce, ServiceNow, SAP, Workday, Vector DBs).
- Experience implementing AI evaluation (Evals), benchmarking and observability tools (e.g., LangSmith, Phoenix, Arize, Weights & Biases, or similar).
- Basic familiarity with cloud infrastructure (GCP, AWS, or Azure) for deploying containerized AI workloads.
Details
- Location: Office - India - Bangalore Bagmane Tech Park.
- Most teams work from the office full time, with flexibility when needed.
- Not eligible for immigration sponsorship.
Read the full description and apply on the company’s own careers page.