AI Systems Engineer
Skills
About the role
This is an AI systems engineering role for someone who can build production LLM applications in Bangalore. You'll lead the design of an enterprise AI agent, covering orchestration, retrieval, evaluation, governance, and reliability. The position suits an engineer with strong Python experience and a background in agentic systems and enterprise data.
What you’ll do
- Lead architecture and development of an enterprise AI agent.
- Create multi-agent workflows with orchestration frameworks such as LangGraph or CrewAI.
- Build pipelines for prompting, retrieval, reasoning, and tool execution.
- Develop prompt engineering and PromptOps practices.
- Create RAG systems for telemetry, benchmarks, and operational data.
- Manage vector search, embeddings, retrieval quality, and context grounding.
- Set up evaluation, regression testing, observability, and quality gates.
- Work with product, engineering, and data science teams.
What they’re looking for
- Three to five years of software engineering or AI product development experience.
- At least two years building and deploying production LLM applications.
- Strong Python skills and knowledge of modern AI application architecture.
- Experience with LangChain, LangGraph, LlamaIndex, or similar tools.
- Experience designing agentic systems, reasoning workflows, and tool use.
- Strong understanding of RAG, vector databases, embeddings, and retrieval optimization.
- A focus on reliability, evaluation, governance, and production operations.
What’s on offer
- Ownership of a strategically important enterprise AI initiative.
- High autonomy over architecture, engineering standards, and AI quality.
- Collaboration with senior research, product, and engineering leaders.
- Exposure to agentic AI, productivity governance, and enterprise analytics.
Questions about this role
How much experience is required?
The posting asks for three to five years in software engineering or AI product development, including at least two years with production LLM applications.
What technologies are required?
The role calls for Python, agent frameworks such as LangChain or LangGraph, RAG, vector databases, embeddings, and evaluation tooling.
Where is the role based?
The posting lists Bangalore.
What does the role build?
It builds an enterprise AI agent for workforce data, operational insights, and productivity intelligence.
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