About this role.
Luxury Presence is hiring a Senior DevOps Engineer to build and operate an AI-native self-service infrastructure platform. The role focuses on developer golden paths, Kubernetes and AWS infrastructure, Terraform and GitOps delivery, CI/CD quality gates, and ephemeral environments. The engineer will own platform components end to end, including observability, on-call, incident management, cost attribution, and reliability improvements. Success requires senior platform engineering judgment, strong cross-team communication, and practical use of AI tools in infrastructure workflows.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
4/5Salary analysis
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Core skills
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Cover letter sample
Dear Hiring Team,
I am excited to apply for the Senior DevOps Engineer role at Luxury Presence. My background in operating production Kubernetes and AWS platforms, building Terraform- and GitOps-based delivery workflows, and owning services through on-call and incident follow-up aligns closely with your self-service infrastructure mission.
I would bring a product-minded approach to platform engineering, creating reliable developer golden paths, practical policy guardrails, observable CI/CD systems, and reusable automation that reduces operational toil. I am also eager to apply AI-assisted development tools thoughtfully to infrastructure delivery, debugging, and operational investigations.
I would welcome the opportunity to help Luxury Presence enable developers and agents to ship changes safely, quickly, and independently.
Sample interview questions
I would describe a platform capability as a product: identify developer friction, define a secure default path, publish a simple interface such as a template or CLI, and measure adoption, lead time, failure rates, and support demand. I would iterate with service teams until self-service reliably replaces tickets without removing necessary controls.
I would use isolated, short-lived Kubernetes namespaces or environments created from versioned infrastructure and application templates, with least-privilege workload identities, scoped secrets, network policies, budget controls, and automatic teardown. CI would expose environment status and machine-readable test results so both developers and agents can diagnose failures quickly.
I would structure Terraform into well-documented, versioned modules with opinionated defaults, enforce plan and policy checks in pull requests, and use a controlled apply workflow such as Atlantis. Drift detection, ownership metadata, state protections, and clear rollback procedures would make the workflow safe at scale.
I would start with clear service-level indicators, actionable alerting, dashboards for pipeline and platform health, and runbooks for common failure modes. During an incident, I would coordinate communication and mitigation, preserve the timeline and decisions, then lead a blameless follow-up that converts recurring issues into automation, tests, or permanent reliability improvements.
I would use AI tools for bounded tasks such as drafting Terraform changes, summarizing logs, investigating Kubernetes symptoms, and generating runbook starting points, while keeping infrastructure changes behind code review, policy checks, least privilege, and validated execution paths. AI output should be treated as a proposal, not an authority, especially for production access or security-sensitive changes.
Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we’re a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business.
The Opportunity
We’re hiring a Senior DevOps Engineer to build the AI-native, self-service infrastructure platform that powers how Luxury Presence ships software. It’s a platform where every developer, human or agent, can validate a change in minutes, understand failures immediately, and ship confidently.
You’ll join a small, high-leverage Infrastructure team with a clear mandate: multiply what every engineer and agent can do through automation, self-service, and guardrails-by-design. The goal is a platform where self-service is the default and human intervention is the exception, and you’ll help make that real.
What You’ll Do
Build and operate the self-service infrastructure platform. Make the right thing the easy thing, and the secure thing the default.
Build the golden paths engineers and agents ship on. Within a technical direction set by the team’s Staff engineers, build and operate the layers they rely on (a unified CI/CD pipeline, GitOps-based delivery with ArgoCD, an IaC module catalog, and scaffolding for new services), owning specific components end to end. The goal is for engineers and agents to provision infrastructure and ship changes within guardrails, without hand-writing Terraform/Kustomize or waiting on a ticket.
Make agents first-class developers. Help generalize our agent isolation pattern into reusable platform primitives: sandboxed runtime, workload identity, audit trails, and approval gates. Every agent action runs on the same identity, audit, ownership, cost-attribution, and approval rails as a human.
Build and operate the validation platform and quality gates. Provide the rails that teams validate changes on before production: ephemeral PR environments with auto-teardown, plus the security, performance, and load-testing gates developers rely on. Implement new gates as coverage grows, keep them fast and low-flake, and drive services onto them. Make gate and test results machine-readable and callable outside the PR flow, so agents and humans alike can act on a failure directly.
Own the reliability and observability of what you build. Create the dashboards and operational controls that make the surfaces you own observable and improvable as throughput grows: gate pass rates, approval-rate and self-service-ratio trends, common failure modes, cost attribution, and DORA metrics surfaced to teams. Carry on-call for those surfaces and run incidents from detection through follow-up, turning recurring toil into automation and runbooks other engineers reuse.
What We’re Looking For
Senior-level experience in SRE, DevOps, or Platform Engineering. You’ve built and operated production infrastructure at scale and can own a significant workstream end to end with limited oversight.
An active, opinionated use of AI development tools (Claude Code, Codex, etc.) in your own infrastructure workflow: Terraform changes, Kubernetes debugging, automation, operational investigations. You have a point of view on where these tools help and where they don’t.
Deep Kubernetes (EKS) and AWS experience (IAM, VPC, ECR, SSM/Secrets Manager, S3, SQS, Lambda, RDS/Aurora).
Strong IaC (Terraform) and GitOps experience, including PR-driven apply workflows (Atlantis or similar) and ArgoCD.
CI/CD depth (GitHub Actions), including caching/parallelism, artifact management, test reliability, and pipeline observability.
Full incident-ownership experience: you’ve carried on-call for systems you built and driven incidents from detection through follow-up.
Excellent cross-team communication: you can translate platform constraints into developer-friendly solutions and documentation.
Bonus Points
Identity, access, and policy-as-code experience: workload/service identity (SPIFFE/SPIRE, OIDC), short-lived credentials, secrets management (Vault), and policy enforcement.
Experience building self-service developer platforms, ephemeral environments, CLIs, scaffolding tools, or internal developer portals (Backstage or custom). You treat infrastructure as a product.
Cost-awareness: you’ve built cost attribution, budgets, or rightsizing into a platform.
Our Tech Stack
Infrastructure: AWS, EKS, Terraform (with Atlantis), Vault, Docker, OPA (Open Policy Agent).
CI/CD: GitHub Actions, ArgoCD + Kustomize (GitOps).
Messaging: Kafka (Confluent Cloud).
Observability: Datadog, OpenTelemetry.
Languages/Apps: Node.js/TypeScript microservices, Python, React front-ends.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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