Staff Platform Engineer

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. Amplitude's Cloud Platform team builds the systems that every Amplitude engineer relies on every day to ship code — and we're rebuilding them for the AI era. As a Staff Platform Engineer, you'll set technical direction for the platform across teams, lead our highest-complexity and highest-leverage initiatives, and shape a platform where AI agents are first-class users alongside humans: kicking off deploys, opening pull requests against infrastructure, and triaging incidents, so a single engineer can get the throughput of a team. You'll operate across team boundaries — partnering with product engineering, fellow Staff+ engineers, and engineering leadership to make Kubernetes and cloud infrastructure effortless across the entire engineering org. You'll build the self-service automation, shared standards, and scalable AWS and GCP infrastructure that let dozens of product teams ship faster, safer, and with less cognitive load — and you'll multiply the engineers around you while you do it. Key Responsibilities Set technical direction — shape platform and domain-level technical strategy that improves developer experience, reliability, security, and cost, and lead the high-complexity, cross-cutting initiatives that deliver it with measurable impact for the organization. Drive clarity through ambiguity. Take on the most loosely-defined problems, validate the critical assumptions early, and create alignment with stakeholders across teams so others can move quickly and confidently — driving cross-team decisions to a timely close and escalating when needed. Build the AI-augmented platform. Design org-wide tooling, guardrails, and policy-as-code that help every engineer get more out of AI-assisted development — infra primitives an LLM can safely reason about and PR against, automated review, and standards that hold as AI changes how code gets written. Own Infrastructure-as-Code standards for Kubernetes, AWS, and GCP using Terraform, Helm, Kustomize, and emerging tooling — setting the patterns other teams adopt and making the platform consumable enough that humans and agents can safely extend it. Evolve our CI/CD backbone (Argo CD / Workflows / Rollouts, GitHub Actions) into shared, well-reasoned standards that make deploys faster, safer, and easier to reason about across the engineering org. Instrument and operate. Drive observability with Datadog and Amplitude, set and raise SLOs for the team, own the dashboards, and drive improvements to the shared services and dependencies that move them. Serve as an escalation point for complex, cross-system P0s, lead incident response, and turn postmortems into durable platform improvements that prevent whole classes of failure. Identify causes, not symptoms. Find the architectural debt that slows multiple teams and build strategies to address it, and recognize when a system must evolve to meet