Lead Performance & AI Tools Engineer, Hybrid

The application window is expected to close on: 12/20/2026 This is a Hybrid role based out of Cisco's San Jose office.

MEET THE TEAM

Cisco’s Developer Platforms and AI Productivity team is dedicated to empowering thousands of engineers by building next-generation internal tools, developer workflows, and autonomous AI agents. As part of Cisco's core engineering organization, our platforms accelerate software delivery speed, eliminate development friction, and ensure high reliability across our global cloud-native portfolio. We are a high-impact, collaborative group of systems engineers, performance architects, and AI practitioners who operate with a startup mindset, treating internal developers as our primary customers. You will have the unique opportunity to pioneer the future of AI-assisted software engineering by integrating coding agents, automated triage, and intelligent performance frameworks at massive enterprise scale.

YOUR IMPACT

As a Technical Leader in Developer Productivity & Performance Engineering, you will serve as the architectural owner for intelligent developer platforms and AI agent tooling. You will turn complex software delivery bottlenecks into high-leverage automation—spanning pull request analysis, CI failure triage, test selection, and release readiness. In this role, you will apply rigorous performance engineering to AI model endpoints and distributed Kubernetes workloads to guarantee optimal throughput and low latency. Success in this position means measurable improvements in developer velocity, shorter cycle times, and the seamless adoption of safe, sandboxed AI workflows across Cisco engineering.

Architect and deploy AI-assisted developer tools: Build intelligent agents for automated PR analysis, CI failure diagnosis, and engineering knowledge retrieval to drastically reduce developer cycle time and manual debugging.

Drive end-to-end performance engineering: Design and implement load, stress, and scalability testing using Python and Locust to optimize latency, throughput, and token generation rates across distributed services and model endpoints.

Establish safe agent execution frameworks: Implement sandboxing, scoped permissions, and confidence thresholds to ensure AI developer tools operate reliably, securely, and transparently.

Unify observability and telemetry pipelines: Correlate metrics from Datadog, Grafana, Splunk, and OpenTelemetry to identify systemic bottlenecks and provide actionable architectural recommendations to engineering leadership.

Building and shipping developer productivity platforms, not just designing AI agents.

Using AI-assisted development to accelerate engineering delivery, rather than only integrating LLMs into applications.

Driving measurable productivity improvements and adoption across engineering teams.

MINIMUM QUALIFICATIONS

Bachelor’s degree in Computer Science, Engineering, or a related STEM field and 10+ years of relevant software engineering experience, Master’s degree and 7+ years, or Ph.D. and 4+ years building distributed platforms.

5+ years of software development experience using Python to design, build, and deploy production internal engineering platforms, automation frameworks, or developer productivity tools

Experience implementing LLM APIs, AI coding assistants, or autonomous agent workflows (e.g., retrieval-augmented generation, PR analysis, or automated failure diagnosis) within engineering delivery pipelines.

Prior experience conducting performance engineering, load testing, and workload modeling for distributed systems using Locust or equivalent load-testing frameworks to analyze latency, throughput, and resource utilization.

Experience operating within Kubernetes and containerized cloud environments, coupled with experience utilizing observability platforms (e.g., Grafana, Datadog, Splunk) and distributed tracing.

Integrating developer tools and automation workflows experience with Git-based source control, pull requests, CI/CD pipelines, APIs, and automated testing frameworks.

Experience leveraging AI coding assistants and LLM-powered development tools to accelerate software development, debugging, and test automation while ensuring correctness, maintainability, and security of generated code.

Ability to independently identify engineering workflow inefficiencies, design and deliver practical automation solutions, and evaluate their effectiveness through developer feedback and measurable productivity improvements.

PREFERRED QUALIFICATIONS

Experience architecting multi-agent orchestration, tool calling, Model Context Protocol (MCP), or vector-based engineering knowledge retrieval systems adopted across multiple teams.

Proven track record defining quantitative developer productivity metrics (e.g., PR cycle time, CI wait time, time to first token) and driving widespread internal tooling adoption.

Experience optimizing and benchmarking LLM inference endpoints (measuring TTFT, token throughput, and GPU utilization) across AWS, GCP, or Azure.

Familiarity with UI/browser performance automation frameworks (Playwright, Lighthouse) and OpenTelemetry distributed tracing standards.

Strong cross-functional leadership, mentorship, and communication skills with the ability to translate complex telemetry data into actionable engineering roadmaps.

Experience building AI-powered developer productivity solutions for code-change impact analysis, dependency-aware test selection, automated CI failure triage, or intelligent release validation.

Experience designing and evaluating AI-agent workflows for accuracy, reliability, cost, latency, and safe execution, including tool-use guardrails, human approval mechanisms, and handling of incorrect or uncertain AI outputs.

Experience integrating automated performance regression detection, baseline comparisons, and actionable performance feedback into pull requests and CI/CD workflows.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:

The starting salary range posted for this position is $186,900.00 to $267,700.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cis