Senior Site Reliability Engineer

About this role

At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale. More than just a workplace, we’re a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following. Our Culture At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are: Mission-Driven: We focus on creating economic and social impact. People-Centric: We care deeply about our team’s growth, well-being, and sense of belonging. Innovative: We embrace change and find better ways to do things together. Globally Connected: We foster collaboration between diverse cultures and perspectives. If you’re passionate about innovation, collaboration, and making a real impact, we’d love to have you on board! Role Summary As a Site Reliability Engineer, you will play a key role in keeping all production systems running smoothly. You will work closely with other engineers and operators to fuse engineering principles, operational knowledge, security, and automation to work towards platform/service production excellence from an angle of infrastructure, reliability, and security. The SRE team owns the foundation of AI Platform’s Core platform - the services and infrastructure that let us deploy to a multitude of public cloud providers and that powers many ML and LLM powered features. We give every other engineering team a reliable base to build on, and we own the software delivery lifecycle end to end: the tooling, patterns, and automation that reduce friction for the whole org. This is an exciting opportunity to grow professionally while contributing to a mission-driven organization. Responsibilities: What you’ll own Reliability of platform(includes ML and LLM workloads) - model serving and inference infrastructure (GPU-backed endpoints, autoscaling, latency and cost tradeoffs), with SLOs, on-call, and incident response that cover models, not just services Observability(includes ML models) - drift and performance monitoring for ML, plus LLM-specific tracing, evals, and guardrails, wired into the same metrics and logging stacks we run everywhere else Company-wide technical direction: shaping the roadmap and building golden paths that raise the baseline for every team Developer tooling and automation that compounds - reusable GitHub Actions, GitOps workflows, Terraform modules - so every engineer ships faster Reusable components packaging common open-source tools (Grafana, Istio, CloudNative stack, and ML tooling such as model registries and feature stores) for teams to deploy in any environment Secure-by-default infrastructure - baking security, compliance audits, cost governance, and audit trails into the platform in close partnership with our lead/backend/staff engineers. Requirements Who you are (must-haves) 5+ years in infrastructure engineering, DevOps, or SRE, operating large-scale, high-availability production systems using Kubernetes Production Operational experience - a live cluster under real load, not a lab. Fluent with Helm, and Terraform or Cloudformation, on at least one major cloud (AWS preferred). Good proficiency in Python or Go or general scripting for automation and tooling(automation with higher language preferred) AI is already in your daily loop - Agentic tooling (Claude Code, Codex, Droid, internal skills) is part of how you ship and not what you are experimenting with. We believe AI tools can be great with human judgement and we want the SRE team to bring the next wave day to day operations. First-principles reasoning - Reasoning from constraints and failure modes naming t

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