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Niche agent/LLM skills but mid-level AI title and Bangalore location create moderate competition.
Agent/LLM engineering skills transfer across industries, so background sensitivity is low.
Explicit 1-6 years and mandatory production LLM/agent experience and tech stack make screening strict.
Own the architecture and orchestration of AI agents including reasoning, planning, tool-calling, and memory management.
Build and ship end-to-end agent products encompassing chat UIs, IDE extensions, CLI tools, backend APIs, and integrations with developer tools.
Define and enforce agent quality standards, mentor junior engineers, manage live releases, and govern citizen-developed agents' safety and standards.
1-6 years hands-on experience building Large Language Model (LLM) or agent systems with production deployments (not just prototypes).
Strong proficiency in Python and/or TypeScript, capable of owning a service end to end.
Experience with agent frameworks or SDKs (e.g., Claude Agent SDK, LangGraph, AutoGen) or custom orchestration.
Work Experience Required: 1-6 years in building LLM or agent systems.
Experience working with AI agent frameworks and node/backend/frontend development technologies indicating full-stack delivery ownership.
Ability to operate hands-on in production settings with responsibility for shipping quality agentic systems and mentoring junior engineers.
Comfortable collaborating cross-functionally with integration architects, MLOps teams, security and compliance to deliver enterprise-grade AI tooling.