Hire DevOps Engineers
Hire DevOps engineers for the release path your team depends on.
RaftLabs embeds DevOps and cloud engineers into product teams that need clear ownership of delivery pipelines, infrastructure changes, observability, cost, or incident readiness. The engineer works inside the client's cloud accounts and review process, with a defined operating boundary and handover plan.
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
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The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
Do releases depend on one person remembering manual steps that are absent from the repository?
Are cloud incidents slow to diagnose because application, infrastructure, and business signals do not meet in one operating view?
Plain answer
Hiring DevOps engineers adds cloud and release capacity while the client keeps day-to-day control. RaftLabs engineers own a defined pipeline, infrastructure, observability, cost, or incident boundary inside the client's accounts and workflow. Planning rates are $6,000 to $6,500 per person monthly, with an initial four-week term.
The deployment is automated until the person who built it is away.
The pipeline runs, but a certificate renewal, database change, or failed rollout still needs private knowledge. Alerts name a server rather than the customer impact. The team has tooling without an owned operating system.
An embedded DevOps engineer should make changes reviewable and recovery teachable. The useful result is not a larger stack. It is a release and incident path the product team can operate.
Relevant cloud delivery proof
- monitored uptime during a four-week campaign record
- 99.9%
- RaftLabs Musgrave project record, not independently audited
- records in a 12-week live platform migration
- 300,000+
- RaftLabs Energia project record
- connected cinema screens on an AWS delivery platform
- 4,000
- RaftLabs ULT Movies project record
The Musgrave campaign, Energia migration, and ULT Movies platform demonstrate cloud delivery under different operating constraints. Their figures describe those products, not a universal reliability promise for an embedded team.
Embedded DevOps capacity fits when the product team can direct priorities but the operating boundary has no durable owner.
Choose a fixed project for one stable migration or pipeline outcome; choose managed operations when you need a provider to own the service around the clock.
The client owns the cloud accounts, application, priorities, and release decisions.
A specific delivery, infrastructure, observability, cost, or incident boundary needs sustained capacity.
Engineers can join the existing review, change, and communication process.
The request is for an undefined promise of zero incidents.
The client needs a fully managed 24-hour operations centre rather than embedded capacity.
Cloud, repository, log, or security access will remain unavailable.
Ownership
What an embedded DevOps engineer can take on
Release pipelines
Build and repair test, build, migration, rollout, approval, and rollback paths in the client's CI/CD system. Manual exceptions become documented controls rather than private memory.
Infrastructure as code
Move agreed cloud resources into reviewed modules with remote state, environment boundaries, plans, and drift checks. Existing working resources are changed only when the risk justifies it.
Observability and incidents
Connect service and infrastructure signals to user impact, define useful alerts, prepare runbooks, and use incident reviews to change the system rather than blame the operator.
Cost, access, and resilience
Inspect spend by workload, right-size with evidence, tighten access, test backup recovery, and make resilience proportional to the product's actual recovery and availability needs.
Do you need embedded DevOps, a fixed project, or managed operations?
Embedded DevOps vs managed operations
| Embedded engineer | Managed operations | |
|---|---|---|
| Control | Client owns priorities, accounts, and releases | Provider owns an agreed operating service |
| Best fit | Platform work inside an existing product team | Defined coverage, response, and service levels |
| Working model | Joins the client's backlog and reviews | Uses a service queue and operating agreement |
| On-call | Only if explicitly scoped with the client team | A core part of the managed contract |
| Alternative | Fixed project for a stable migration or pipeline | Internal hire for permanent operating leadership |
Do not buy an embedded engineer and expect a managed service by implication. Coverage, authority, escalation, and response expectations need explicit owners.
Onboarding
From platform bottleneck to owned operating work
The first four weeks test access, safe change, operating evidence, and knowledge transfer.
- Before start01
Define the platform boundary
Choose the release, cloud, observability, cost, security, or incident work the engineer will own. Agree the current baseline and who approves risky changes.
- Week 102
Match the role and access
Review cloud and tooling depth, then prepare accounts, repositories, environments, secrets, logs, and team access. Begin with a bounded change that reveals the delivery path.
- Weeks 1-403
Change infrastructure safely
Work through reviewed code, plans, tests, rollout, monitoring, and rollback inside the client's delivery process. Record why each change is made and how operators verify it.
- End of term04
Review and hand over
Assess release and operating evidence, update runbooks, and review the next-term need. Continue, change the boundary, adjust the role, or finish with ownership returned cleanly.
Where embedded DevOps engagements fail
- Tools replace an operating decision
- Terraform and Kubernetes cannot decide recovery time, access authority, or acceptable deployment risk. Product and engineering leaders still own those choices.
- Everything pages someone
- An alert needs a response, owner, and user impact. Remove noisy signals and test the path from detection through recovery.
- Infrastructure code is never applied
- A repository can look current while consoles drift. Review plans, control application, and detect manual changes instead of treating files as proof.
- On-call is assumed
- Embedded work does not automatically provide round-the-clock coverage. State hours, escalation, access, authority, and response expectations in the engagement.
Monthly model
Plan on $6,000 to $6,500 per person each month.
Start with one DevOps engineer and a named platform boundary, or use a lean team when QA and delivery coordination are also required.
Fixed-scope DevOps work is priced separately when a pipeline, migration, infrastructure module, or observability outcome has a stable acceptance boundary.
Starting investment
$6K-$6.5K per person monthly
A lean team starts around $12,000 to $15,000 per month. The initial term is four weeks; role mix, allocation, and coverage set the final rate.
No automatic platform complexity
The engineer should justify new orchestration, tooling, or cloud services against the workload and the team's ability to operate them.
Handover stays in your accounts
Infrastructure code, pipeline configuration, tests, decisions, dashboards, and runbooks remain in the client's systems throughout the engagement.
Related team options
Choose the role or delivery model
- 01
Dedicated teams
Compare general staff augmentation, lean delivery teams, role mix, monthly pricing, and the first four-week term.
- 02
Dedicated backend team
Add API, data, integration, background-job, and server-side reliability capacity inside the product team.
- 03
Cloud application development
Choose a fixed delivery engagement when the application and cloud outcome can be scoped as one project.
Work with us
Show us the release or incident path that depends on one person.
Bring the cloud boundary, current tooling, recent failure, and team process. We will tell you whether embedded capacity or a fixed project fits.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
Common questions
Choose a boundary the team can review: a deployment path, cloud environment, infrastructure-as-code module, observability stack, cost problem, or incident-readiness gap. The engineer may work across systems, but a named outcome prevents the engagement from becoming a stream of unrelated access and support tickets.
Kubernetes is useful when the workload and team need its scheduling, rollout, isolation, or scaling controls. It also creates an operating surface that must be patched and understood. Managed containers, serverless services, or a simpler deployment target are often better for a small number of stable services. We assess the workload first.
Yes. The first review separates resources already defined in code from manual or undocumented changes, then identifies the highest-risk path. We do not require a rebuild merely to standardise tooling. Changes should be staged, reviewed, tested, and reversible in the client's accounts.
The engineer can implement access boundaries, encryption settings, logging, backup, change records, and evidence collection that support the client's control framework. RaftLabs does not certify compliance or replace the client's security, legal, or audit owners. Required controls and approval authority must be defined by those owners.
DevOps as a service is four different engagements, and most disappointing contracts come from buying one while needing another. Automation is a bounded deliverable: pipelines built and handed over. Managed service is ongoing operation: someone else runs it. Support is reactive: you keep ownership, they help. Transformation changes how your teams work. Decide which model you need before comparing vendors — the price and the contract look completely different for each.
Demand baseline metrics in week one: how often you deploy, how long changes take to reach production, how often releases fail. Then measure against them. If you bought transformation and deployments still take as long as they always did, you bought a document, not a change. Ask the incident-response question: if the provider cannot state what happens when production breaks — who responds, how fast — you are buying optimism, not reliability.
Deliverables defined as artefacts, not outcomes. Infrastructure as code in your repositories from day one. A named escalation path with response times. Knowledge transfer as a scheduled deliverable, not a final-week handover. Exit assistance at agreed rates. Explicit security and access boundaries, including how access is revoked when an engineer rolls off. Any provider who resists making knowledge transfer explicit is building dependency, not capability.
Use $6,000 to $6,500 per person per month for planning. A lean team with engineering plus part-time project and QA support starts around $12,000 to $15,000 monthly. Role mix, allocation, duration, on-call expectations, and specialist depth set the final rate before the initial four-week term.