Senior DevOps Engineer – Autonomous Systems

About the role

We are looking for a senior engineer who lives at the intersection of production operations and intelligent automation. You will own shift responsibilities, command incidents, and build autonomous agents that eliminate manual toil on a platform serving Fortune 100 brands.

Key responsibilities

• Run the on‑call shift: triage, diagnose, mitigate, restore services and escalate when needed.
• Design, ship, and iterate autonomous workflows that handle alert pre‑triage, deployment validation, self‑healing and post‑incident analysis.
• Guard every production change with quality gates, proven rollback procedures and cost‑action controls.
• Investigate root causes, implement systemic fixes and track them to completion.
• Convert manual fixes into reusable agent rules, guardrails or runbooks to expand the autonomous layer.
• Document decisions, procedures and operational context for both agents and humans.

Required profile

• 5+ years in production‑facing roles such as SRE, DevOps, Platform Engineering or Cloud Infrastructure on large‑scale SaaS.
• Deep AWS experience at scale (multi‑AZ, multi‑account, infrastructure automation, gated change management, rollback discipline).
• Self‑directed mindset: set priorities, identify high‑leverage gaps and close them without waiting for assignments.
• Hands‑on AI‑native practice: build and evaluate autonomous agents using tools like Claude Code, Codex, Warp or custom frameworks.
• AWS Solutions Architect – Associate (or equivalent) certification.
• Fluent, precise English for incident communication and post‑mortems.
• Willingness to participate in shift‑based on‑call coverage.

Required skills

• AWS (multi‑AZ, multi‑account, automation, rollback)
• Observability stacks: Grafana, Prometheus, Datadog
• Alerting & incident tools: PagerDuty, OpsGenie
• AI/automation tools: Claude Code, Codex, Warp, custom agent frameworks
• Azure familiarity

What we offer

• Fully remote, distributed global team.
• Unconstrained tooling and investment in larger models or new technologies to support autonomous workflows.