AI-First DevOps Engineer (Senior)

Role:AI-First DevOps Engineer (Senior)Location:Mountain View, CAType:ContractPaved Road & Agentic Delivery AutomationIntuit PDX • Development Efficiencies / Modern SaaS AIRStaff Augmentation - Expert Hands-On Individual Contributor • Reports functionally to Intuit Engineering Lead (does not lead the engagement) • Location / Model: TBD • Duration: 6/12 months, extendableAbout the TeamThe Development Efficiencies pillar owns the paved roads, PDLC velocity, and self-serve tooling behind Intuit's 8x developer velocity gain, built on Modern SaaS AIR - Intuit's AI-native dev platform on Kubernetes, Argo, Istio, Envoy, and AWS. Intuit is an active CNCF/Argo contributor; this role works on the same stack upstream.The Problem This Role Exists to SolveDevelopment is AI-accelerated; delivery must keep pace. Every human-gated step in CI/CD, environments, and release process erodes the 8x gain. This role makes the delivery pipeline itself AI-first: paved-road pipelines where agents diagnose failures, triage PRs, provision environments, and automate release toil - directly serving the FY26 Reduced Human Effort and PR Merge Velocity KPIs.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 PDX metric). Must-Have Qualifications7+ 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 Intuit KPI. Nice-to-HaveSLSA / 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.