Back
High competition: generalist senior AI title, mid experience band, Bangalore location, and broad multi-skill requirements.
Medium: specialized LLM/agent production skills are transferable but still require domain-specific experience.
High: explicit 1–6 years, mandatory hands-on LLM/agent production experience, and specific tech stack requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own the design and architecture of AI agents including reasoning, planning, tool-calling, memory, and user interaction surfaces (chat UI, IDE extensions, CLI tools).
Ship and deploy end-to-end agent products integrating backend APIs, developer tool integrations, and ensure live operational quality with MLOps/eval collaboration.
Lead and mentor junior engineers, enforce governance and quality standards, and maintain self-service tooling and support for citizen developers building AI agents.
1-6 years hands-on experience building and shipping LLM or agent systems to production (not prototypes).
Strong skills in Python and/or TypeScript; experience owning full service lifecycle end-to-end.
Hands-on with agent frameworks or SDKs (e.g., Claude Agent SDK/MCP, LangGraph, AutoGen) or custom orchestration.
Experience designing REST, GraphQL, streaming/WebSocket APIs; solid grasp of traditional ML and LLM/agent-based AI approaches.
Experienced in architecting and shipping complex AI agent systems oriented to developer tooling and platform environments.
Comfortable with hands-on coding, debugging, mentoring, and defining operational standards and governance for AI products.
Skilled collaborator working with cross-functional teams (Integration Architect, MLOps, security/compliance) in a global, structured engineering environment.