Platform Engineer (Agent Release)

About this role

Join the Future of Security at Netskope

Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.

At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.

Visit Careers at Netskope to learn more. Follow us on LinkedIn and Instagram.

An agent doesn't go from a developer's laptop to production in one step here — it moves through a staged pipeline with real gates at every stage, then spends its first two weeks in production under close review before anyone trusts it to act on its own. As a Senior Agent Release Engineer, you'll own that entire path: the CI/CD pipeline every agent and every model change moves through, the automated checks that decide whether a release is safe to promote, and the rollback plan for when something isn't. You'll also own model tiering — making sure each agent is running on the model tier that actually fits its task, since that's one of the biggest cost levers on a platform running well over a hundred agents at once. If you like turning "we hope this works" into "here's the automated gate that proves it," this is that role.

Skills and competencies:

• Own and continuously improve the CI/CD pipeline every agent and every model or prompt change moves through, from initial commit through sandbox, development, and staging, before anything reaches production.

• Design and maintain the automated gates that decide whether a release is safe to promote — evaluation score thresholds, security scan results, guardrail test results — so a human isn't manually eyeballing test output before every promotion.

• Own progressive rollout for model and agent changes: canary a change to a small slice of traffic or sessions first, watch the quality and cost metrics live, and only promote to full traffic once those metrics hold.

• Build and maintain the rollback path for every stage of the pipeline, so that a bad release can be reversed in minutes, not hours, and so the trigger conditions for rollback are automatic rather than someone noticing a problem by chance.

• Own model tiering across the agent fleet: routing agents to the model tier that actually fits their task complexity, and adjusting that routing as usage patterns or model pricing change.

• Manage the shadow-period process for newly promoted agents, making sure the right metrics and review checkpoints are actually in place and visible before an agent moves from shadow to fully autonomous operation.

• Run model version regression testing whenever a new model version becomes available, confirming existing agents don't silently degrade before that version gets adopted anywhere in production.

• Partner with the Agent Runtime Engineer on the runtime side of releases to quickly troubleshoot issues in case of a bad rollout.

Must-Have:

• At least 5 years in CI/CD, release engineering, or MLOps, including 1–2 years releasing LLM or agent-based systems specifically.

• Has designed and run a progressive rollout strategy (canary, shadow, or blue-green) for something stateful or model-driven, with automatic rollback triggers built in from the start, not a person noticing a problem and rolling back by hand.

• Has gated a release on evaluation scores before, treating a regression as a hard stop the same way a failed test would, and can design that same kind of check to catch a new model version quietly degrading an existing agent before it touches production.

• Strong Python (or similar) and solid infrastructure-as-code skills. Terraform, CDK, GitHub Actions, or…