Senior AI Tools & Performance Engineer

Cisco Systems, Inc.

Milpitas (CA)

Hybrid

USD 187,000 - 268,000

Full time

3 days ago

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Job summary

Cisco Systems, Inc. is seeking a Technical Leader for Developer Productivity & Performance Engineering in a hybrid role based in San Jose.

You will own intelligent developer platforms and AI agent tooling, improving velocity through automated PR analysis, CI failure triage, and performance optimization. You will lead design and experimentation on AI-assisted workflows, ensure safe execution, and drive observability across distributed Kubernetes workloads.

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related STEM field with 10+ years of software engineering experience.
5+ years of software development experience using Python to design, build, and deploy production internal engineering platforms or developer productivity tools.
Experience implementing LLM APIs, AI coding assistants, or autonomous agent workflows within engineering delivery pipelines.
Prior experience conducting performance engineering, load testing, and workload modeling for distributed systems using Locust or equivalent tooling.
Experience operating within Kubernetes and containerized cloud environments with observability platforms like Grafana, Datadog, Splunk and OpenTelemetry.
Experience integrating developer tools, Git-based workflows, CI/CD pipelines, APIs, and automated testing frameworks.
Ability to independently identify engineering workflow inefficiencies and deliver automation with measurable productivity improvements.

Responsibilities

Architect and deploy AI-assisted developer tools to reduce developer cycle time and debugging effort.
Drive end-to-end performance engineering to optimize latency and throughput across distributed services.
Establish safe execution frameworks with sandboxing and guardrails for AI tools.
Unify observability pipelines to identify bottlenecks and guide architecture decisions.
Build and shipping developer productivity platforms, not just AI agents.
Use AI-assisted development to accelerate engineering delivery across teams.
Drive productivity improvements and adoption across engineering organizations.