Backend (Python)

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 engineering organization more effective. What Youll 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 Google Cloud Platform for scale, reliability, and performance. Drive engineering excellence through code quality standards, design reviews, automation, and CI/CD best practices. Collaborate across teams Product, AI, and Security to align architecture with business objectives. Be a mentor and multiplier, guiding engineers through architecture decisions, trade-offs

Do you have experience in System design?, and delivery. Partner with leadership to align engineering strategy with product objectives and technical roadmap. What Were Looking For 6+ years of software engineering with 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 Google Cloud Platform compute, storage, IAM, networking, 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 (Claude, LiteLLM), AI gateways, agent frameworks and being able 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, Google Cloud Platform, 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.