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Global Infrastructure and Platform Onsite – Palo Alto, CA (5 days/week)
About the Team
Our client's Enterprise AI team is their internal AI enablement engine. They evaluate where AI can make a real difference, build the platforms and patterns that make adoption easy, and help engineering teams across the organization work smarter and faster. Operating at the intersection of applied AI, distributed systems, and enterprise operations, this team's mission is to make a top-tier technology company more efficient — one AI-powered workflow at a time.
This is a high-impact, high-autonomy team where you'll work closely with engineering, product, and operations teams to bring AI capabilities to life.
About the Role
We are hiring a Senior Software Engineer to design, build, and operate the platform and backend systems that power our client at scale. You'll own core infrastructure — from Kubernetes and cloud-native services to APIs and developer tooling — and work closely with product, AI, and security teams. This is a hands-on, high-ownership role where you write production code, design systems, lead code reviews, and make the broader engineering organization more effective.
What You'll Do
Own end-to-end delivery of major platform initiatives, from design through deployment and post-launch success
Own Kubernetes at depth — clusters, networking, operators, container lifecycle, and multi-tenant orchestration
Design, develop, and optimize distributed services and cloud-native infrastructure on AWS and/or GCP for scale, reliability, and performance
Drive engineering excellence through code quality standards, design reviews, automation, and CI/CD best practices
Collaborate across Product, AI, and Security teams to align architecture with business objectives
Serve as a mentor and force multiplier, guiding engineers through architecture decisions, trade-offs, and delivery
Partner with leadership to align engineering strategy with product objectives and the technical roadmap
What We're Looking For
6+ years of software engineering with a deep backend and infrastructure focus
Strong programming skills in Python and/or Go — you ship production code, not just scripts and configs
Deep, hands-on Kubernetes experience building and operating clusters, not just deploying to them
Proven experience designing and operating distributed systems in production
Cloud-native fluency across AWS and/or GCP — compute, storage, IAM, networking, xsgimln and managed services
Experience with infrastructure-as-code (Terraform or similar) and CI/CD pipelines
Familiarity with applied AI tooling and patterns — agentic AI tools (e.g., Claude, LiteLLM), AI gateways, and agent frameworks — and the ability to build backend services that integrate with them
Strong system design and architectural judgment
Clear communicator who partners well across product, security, and AI teams
Nice to Have
Observability stacks — Prometheus, Grafana, Datadog, OpenTelemetry
Multi-cloud or hybrid infrastructure experience (AWS, GCP, on-prem)
Familiarity with API gateways, AI gateways, and policy/authorization frameworks (ABAC, OPA)
Service mesh or platform-as-a-service design experience
Track record of improving engineering productivity at scale