Sr Staff Agentic AI Engineer - Bengaluru, Karnātaka, India

Job Summary

Build the Consoles

• Design and build persona consoles including decision inboxes, review surfaces, approval queues, and commitment views.
• Make agent actions, rationale, confidence, and human intervention needs clear to busy decision-makers.
• Work closely with UX on interaction details and reduce approval fatigue through design.

Value and Telemetry

• Build live dashboards covering cycle time, throughput, quality, adoption, agent health, and cost.
• Create executive value boards that show committed versus realized value without manual curation.
• Instrument the platform so its metrics do not need to be assembled manually.

Full-Stack Engineering

• Build backend-for-frontend services, APIs, and event consumers connecting consoles to the orchestrator and enterprise systems such as Jira.
• Implement enterprise-grade authentication and authorization with SSO and OAuth while respecting data boundaries.
• Ship on the approved enterprise React stack with CI/CD, automated testing, and observability as defaults.

Engineering Standards

• Use agents in the development workflow and feed friction back into the platform.
• Set reusable frontend and backend-for-frontend patterns for components, state, accessibility, and performance.
• Maintain a fast, tested, and observable stack as the number of surfaces grows.

Required Qualifications

• Six to ten years of professional software engineering experience, including ownership of large-scale production systems.
• Significant hands-on experience designing and deploying LLM-powered applications, AI agents, or intelligent automation platforms.
• Experience designing evaluation frameworks, testing strategies, and governance models for AI-enabled systems.
• Expert-level proficiency in Python, Java, or TypeScript.
• Strong background in distributed systems, APIs, platform engineering, cloud-native architectures, and event-driven systems.
• Experience leading technical initiatives across teams.
• Strong communication skills for explaining complex AI systems to technical and non-technical audiences.
• Proven ability to influence architecture, standards, and engineering direction.

Preferred Qualifications

• Deep experience with agent frameworks such as MCP, A2A, LangGraph, OpenAI, Anthropic, Bedrock, or Vertex AI.
• Experience building developer platforms, internal engineering products, or enterprise orchestration systems.
• Experience with RAG architectures, embeddings, vector databases, knowledge graphs, or enterprise search.
• Experience leading AI governance, privacy reviews, security reviews, or responsible AI initiatives.
• Technical leadership demonstrated through open-source contributions, patents, publications, or industry speaking.

Success Measures

Why This Role