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Senior Engineer

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Hybrid

Senior Engineer

Kornferry

Senior Engineer

Skills

Google Cloud PlatformAIAWSKubernetesAzure

11 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

16 October 2026

What they need


We're looking for someone with software engineering experience of 6+ years, with hands-on experience building LLM-powered or agent-based systems in production.

Technical Skills

  • Solid software engineering fundamentals: system design, API design, data modelling, and clean, maintainable code.
  • Experience building and running production systems in the cloud (AWS, GCP, or Azure), including containers, Kubernetes or similar, and infrastructure as code.
  • Hands-on experience with distributed systems: queues, async workflows, concurrency, reliability, and failure handling.
  • Practical experience building with LLMs: tool use, agents, prompt and context engineering, RAG, and evaluation.
  • Familiarity with agent protocols and ecosystems (e.g., MCP) and with using AI coding tools day to day.

Leadership & Ownership

  • Comfort working independently and handling ambiguity: you can take a loosely defined problem, scope it, and drive it to production.
  • Clear written and verbal communication, including explaining trade-offs to both technical and non-technical audiences.
  • At the senior level, we also expect you to lead projects and set technical direction, mentor other engineers, define evaluation and quality standards, and influence architecture across teams.

Mindset & Collaboration

  • Growth mindset curious, always learning, and open to feedback.
  • Works closely with the engineers who use these tools every day; you help the whole organization build software better and faster.

Nice to Have

  • Experience with trace analysis or log mining to find and fix agent failure modes.
  • Experience building internal platforms or SDKs that other teams adopted.
  • Background in observability, CI/CD, or developer productivity tooling.
  • Experience with model routing, cost optimization, or prompt caching.
  • Open-source or public contributions in agent tooling or LLM infrastructure.

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