Senior DevOps Engineer (AI)

AI-First DevOps Engineer (Senior)

About the Team

The Development Efficiencies pillar owns the paved roads, PDLC velocity, and self-serve tooling behind an 8x developer velocity gain, built on Modern SaaS AIR — an AI-native development platform on Kubernetes, Argo, Istio, Envoy, and AWS.

An active CNCF/Argo contributor, this role works on the same stack upstream.

Key Responsibilities

• Build and extend paved-road CI/CD: pipeline templates, golden paths, and policy-as-code gates that product teams adopt self-serve — no tickets, no mandates.
• Build Argo-based GitOps delivery (CD / Workflows / Rollouts): progressive delivery pipelines including the paved road for shipping AI agents to production the way teams ship microservices — AI Model Deployment Events/Time is a tracked KPI.
• Build agentic delivery automation into the pipeline: failure-diagnosis agents, PR triage and review-assist agents, environment provisioning automation, change summarization — measured against FY26 Reduced Human Effort.
• Extend developer inner-loop tooling: cloud workspaces, fast local-to-cluster iteration.
• Instrument delivery: PR merge velocity, AI-assisted code share, and DORA-style flow metrics feeding org KPIs.
• Harden the supply chain on the paved road: signing, provenance, SBOM as pipeline defaults.
• Seam with SRE: you build the rollout pipeline; SRE owns canary analysis and rollback gates — you integrate their gates, not define them.
• Production support for delivery tooling; self-serve docs and inner-source contributions (tracked metric).

Must-Have Qualifications

• 7\+ years DevOps/release/platform engineering; has designed enterprise CI/CD systems, not just operated them.
• Production depth in Argo (CD, Workflows, Rollouts) and the GitOps operating model; Kubernetes \+ AWS at scale.
• IaC (Terraform or equivalent) and policy-as-code (OPA / Kyverno or equivalent) in production.
• Strong Go or Python — delivery tooling built as products, with tests and observability.
• Hands-on agentic/LLM automation applied to the SDLC: has shipped agents or LLM-powered bots into a delivery flow — pipeline triage, review assist, automated remediation — not just personal Copilot use.
• Fluent AI-assisted development workflow — AI-assisted code in PRs is a tracked KPI.

Nice-to-Have

• SLSA / supply-chain security depth; Backstage or internal developer platform (IDP) experience.
• Ephemeral / preview environment platforms at scale; FinOps.
• MCP tool integrations; CNCF or other open-source contributions.

Top 10 LinkedIn Skills

1. DevOps
2. Kubernetes
3. GitOps
4. Argo CD
5. CI/CD
6. Terraform
7. AWS
8. Python or Go
9. Platform Engineering
10. Agentic AI / AI Automation