Platform / Site Reliability Engineer

Create a small set of supported patterns for customer-facing services, connectors, scheduled jobs, data-processing pipelines, model-backed workloads, and evaluation runs. Define the contracts for environments, compute, state, networking, delivery, secrets, telemetry, failure handling, and recovery without forcing every workload into an inappropriate stack.

Make it straightforward for an engineer to create an environment, ship a safe change, understand a failed deploy or job, get the right access, recover a system, and know who owns the result. Build useful self-service and escape hatches while making unsupported paths and exceptions explicit.

Connect service, queue, job, pipeline, and model telemetry to the outcome that matters. Establish practical objectives, alerts, incident mechanics, replay and recovery paths, and reviews that remove recurring failure classes instead of only documenting them.

Expose cost and capacity in workload-relevant units, then improve them without hiding reliability, security, quality, or developer time. Work with Security to implement least privilege, secrets, logging, backup, deployment, and audit controls whose evidence comes from the systems that actually enforce them.

Establish Sunset's current platform, workload, reliability, ownership, toil, recovery, cost, and technical-control baseline

Build reusable infrastructure-as-code modules, runtime templates, deployment workflows, environment contracts, and operational tooling

Create supported paths for customer-facing services, asynchronous and batch jobs, data pipelines, and model-backed workloads

Improve deploy safety, workload visibility, backup and recovery, incident response, replay, rollback, and durable remediation

Work with engineering teams to define useful service and pipeline objectives, ownership, escalation, and recovery paths

Build self-service for common infrastructure, environment, access, deploy, debugging, and recovery work without becoming a central approval queue

Make cloud and vendor cost understandable by service and workload and improve efficiency within explicit reliability and security bounds

Partner with Security on cloud identity, secrets, isolation, audit logging, vulnerability response, incident readiness, and automated control evidence

Support employees and contractors through bounded access, safe environments, release controls, documentation, and timely removal of authority

Use AI tools deeply for platform engineering and operations while verifying generated code, plans, queries, state changes, and incident conclusions

Sunset's environments, runtimes, deploy paths, service and pipeline owners, reliability risks, recovery gaps, manual work, and infrastructure costs are visible and prioritized

One consequential failure or toil class is materially reduced in your first 90 days, and another team can use the resulting paved road without case-by-case help

Product, data, and AI teams can ship and understand their systems faster while retaining clear operating ownership

Priority services and pipelines have useful objectives, actionable telemetry, tested recovery paths, and incident learning that removes recurring failures

Common platform work becomes self-service while exceptions remain explicit, owned, monitored, and time-bounded

Cloud cost and capacity are understandable in workload-relevant units and improve without hidden reliability, security, or developer-time regressions

Security and customer-trust evidence becomes easier to produce because it reflects current technical controls

You have personally owned production cloud infrastructure and delivery or reliability systems across multiple services, including an asynchronous, batch-data, or model-backed workload

You are a strong software engineer who is comfortable changing application, platform, and infrastructure code and operating the result in production

You can reason from user impact through dependencies, state, telemetry, incident response, recovery, and durable remediation

You have built paved roads other engineers adopted because they made real work easier, not because a platform team required them

You understand both long-running services and high-volume or scheduled workloads and know where their reliability models should differ

You can make pragmatic tradeoffs among delivery speed, least privilege, isolation, recovery, developer experience, and unit cost

You are effective in an early-stage environment where the first step is often to establish ownership and a trustworthy baseline

You can lead calmly through ambiguous incidents, communicate clearly, and leave the system and operating model stronger afterward

You use modern AI engineering tools fluently and verify generated infrastructure, queries, code, and operational conclusions before they affect production

You want a deployment or cloud-administration role where product teams hand systems to you to operate permanently

You prefer designing a platform in isolation to learning how engineers, services, pipelines, and customer deliveries actually work

You measure platform success by migration, ticket, dashboard, or uptime counts without connecting them to adoption, reliability, recovery, and user impact

You want to standardize every workload on one stack regardless of its state, scale, failure, or recovery requirements

You do not want AI tools to be part of your daily engineering and operational workflow

Experience as an early platform or SRE hire at a fast-growing company

Experience with AWS, Terraform, container runtimes, workflow orchestration, and observability systems

Experience with high-volume data processing, model serving, evaluation jobs, GPU workloads, or machine-learning platforms

Experience improving developer environments, preview systems, CI/CD, progressive delivery, or internal developer platforms

Experience with replayable pipelines, backup and restore, disaster recovery, capacity planning, or cloud-cost allocation

Experience implementing technical controls and automated evidence for SOC 2 or enterprise customer requirements