The forward-deployed engineer who owns delivery end to end: pipelines, infrastructure as code, and systems your team can operate, built inside your team and handed over documented.
Why this role exists
When releasing software is risky, teams release rarely, and rarely-released software is riskier still. The way out is not a bigger process. It is an engineer who owns the path from commit to production and makes it safe to walk often.
Most teams do not need a platform department. They need one senior engineer who owns the pipelines, environments and incident response, works inside their codebase, and leaves the system running without us. That is exactly what this role is.
What this engineer owns
The engagement starts with a single senior engineer inside your team and grows only when the problem justifies it. These are the commitments behind the role; exact scope is agreed with your team.
Your DevOps engineer takes a change from commit to production: build, test, deploy, rollback and monitoring. They build the pipelines, own the on-call when it breaks, and stay answerable for release health.
What to verify: Ask who owns a change from commit to production, and who is paged when deploys fail.
One command, or no command at all: pipelines that build, test and release the same way every time. Rollbacks are rehearsed, not improvised, and a bad deploy is undone in minutes.
What to verify: Ask how a deploy is rolled back, and when rollback was last rehearsed.
Environments, networking and permissions live in versioned code with review and CI. No undocumented console changes, and every environment can be rebuilt from the repository.
What to verify: Ask whether a new environment can be built from the repository alone, and who reviews infrastructure changes.
Cloud spend is tagged, attributed and reviewed. The engineer rightsizes what is oversized, shuts down what is idle, and puts guardrails on what can grow.
What to verify: Ask what the monthly cloud spend is by service, and what the last cost fix saved.
Alerts that page for real problems only, runbooks that anyone can follow, and post-incident reviews that change the system rather than blame people. Downtime becomes shorter each time.
What to verify: Ask what the last incident changed, and how long detection took.
Every pipeline, environment and runbook lives in your repository with written rationale. When the engagement ends, your team ships and operates the system without us in the loop.
What to verify: Ask where the runbooks live, and who on your side can ship after handover.
How they work
The loop is simple and strict: build the change, test it, deploy it through the approval gate, and operate it with the alerts that prove it is healthy.
AI in the engagement
AI is not a separate offering bolted on. It is part of how this engineer works, and the judgment they bring is part of what your team absorbs.
AI tooling speeds up pipeline scaffolding, Terraform drafts and log analysis. What ships is configuration the engineer has read, understood and taken responsibility for.
AI can draft a module quickly, but the engineer checks it against the real environment: permissions, networking and blast radius are validated before it applies to anything shared.
AI-assisted changes go through the same review, tests and CI as everything else. Nothing reaches production because it looked finished.
The engineer ships small, frequent changes behind flags where possible, so every deployment is easy to verify, roll back and learn from.
Working principles
Written scope, reviewed changes and visible trade-offs decide whether an embedded engineer actually works. We make those commitments explicit rather than implied.
The environments, deliverables and on-call expectations are written down before the first commit, and changes to them are agreed, not assumed.
Every pipeline and infrastructure change goes through review and CI like the rest of the codebase. The engineer is a team member, not an outside black box.
When speed, cost and reliability conflict, the engineer shows the options and lets you decide, rather than picking quietly.
You work with the same engineer for the engagement, not a rotating bench. Continuity is what makes judgment about your systems compound.
Security & trust
This role touches your production systems, your customers and your cloud spend. Access, change boundaries and credentials are agreed in writing before the first commit.
The engineer gets scoped access to the cloud accounts, clusters and repositories the work needs, nothing more, and access is reviewed and revoked at the end of the engagement.
Development and testing use isolated environments and synthetic data. Production credentials never leave your secret manager.
Credentials and keys live in your secret manager, never in code, pipelines or chat, and are rotated when the engagement ends.
Deploys, infrastructure changes and access grants are logged, so any change to production can be traced to a person and a reason after the fact.
Working arrangements
The engineer works remotely inside your rituals, in your repositories and cloud accounts, with infrastructure running on systems you control.
The engineer joins your stand-ups, reviews and incident calls from remote, and works in your repositories and cloud accounts as a team member would.
Cloud accounts, clusters and pipelines stay yours, with your credentials and your logging. We do not route your workloads through infrastructure you have not approved.
What the engineer may access, what may change without review and what requires your sign-off are agreed in writing before development starts.
For migrations, critical launch windows or working through an incident live, on-site time is arranged deliberately.
How it starts
A paid two-week sprint proves the working relationship before anything longer is discussed. If it does not show real progress, you walk away.
Week one starts with the real systems: how deploys actually happen, what breaks, what the alerts wake people up for, and what the cloud bill says. The engineer sits with your team and traces the paths as they actually run.
One goal in writing: for example, one service deployed through a tested pipeline with monitoring, alerting and a rehearsed rollback. Success criteria are agreed before building starts.
The engineer builds inside your platform, opens small reviewed changes, and shows you the pipelines and environments working, including what did not work, at the end of each week.
At the end of the sprint you see what shipped, the deploy metrics and the runbooks, and decide together what comes next: extend, hand over or stop.
The major clouds and the orchestration, CI and infrastructure-as-code tools commonly built on them. The engineer fits your existing stack rather than insisting on a migration.
Yes, and that is the default. They work inside your repositories and accounts, follow your conventions and improve what they find, rather than starting something parallel.
No. They build and improve the delivery foundations your team depends on and hand them over documented, so your engineers spend their time on product instead of firefighting infrastructure.
Boundaries are agreed in writing before the sprint starts. Within the engagement, the engineer owns the systems they build and joins incident response for them; permanent on-call coverage is a separate, explicit arrangement.
No, but someone on your side owns the outcome. The engineer works with your technical lead, and hands the platform over with documentation, tests and a documented operating process.
The sprint is a fixed, paid engagement agreed before it starts, and its scope is written down. If it does not show real progress, you walk away with everything built so far in your repository.
Let's talk
Tell us about the systems, the deploy process and what wakes people up at night. We will help define a first sprint goal and the evidence needed to judge it.