Architect and operate our Kubernetes platform on AWS – scaling, networking, cost, and reliability
Own infrastructure as code (Terraform) so environments are reproducible, auditable, and fast to evolve
Build the foundations that let the team provision and scale services without friction
AI agent platform – managing and scaling agents at volume
Operate and scale the orchestration layer (Temporal) that runs dozens of agents in parallel
Tune the platform for the unusual load profile of agent workloads – bursty, long-running, data-heavy, latency-sensitive
Give engineers the primitives to deploy, version, observe, and roll back agents safely under enterprise SLAs
CI/CD and developer experience
Own build and deploy pipelines end-to-end – fast, safe, boring releases
Invest in DX as a first-class product: the team treats developer experience as leverage, and you set the bar
Reduce the time from merged to in production and from idea to running experiment
Observability and reliability
Build monitoring, alerting, and tracing that make production legible – for services and for agents
Own incident response and the reliability practices that keep enterprise customers SLAs intact
Turn incidents into systemic fixes, not repeated firefighting
Security and compliance
Own secrets management, hardening, and the day-to-day security posture of the platform
Support our compliance commitments (we are Mastercard-certified, operating in fintech – the bar is high)
Build security into the pipeline so it is the default, not a gate
Strong DevOps/platform/SRE experience at a company with a real engineering culture (FAANG, unicorn, or a well-established startup with high standards)
Deep Kubernetes and AWS – you have architected, scaled, and debugged production clusters, not just deployed to them
Infrastructure as code in your bones – Terraform or equivalent, with strong opinions on reproducibility and auditability
CI/CD ownership – you have built pipelines that engineers trust and rarely think about
Production observability and incident response at meaningful scale
Comfort with and curiosity about AI/LLM workloads. We are an AI-native company; you should be using AI in how you work, and excited to operate the infrastructure agents run on
