Core engineering
Hire Platform and DevOps Engineers
Engineers who make deployment boring, so shipping stops being an event and becomes a routine.
A platform or DevOps engineer automates the path from commit to production and keeps it fast and reliable: CI/CD, infrastructure as code, observability and incident response. Hire one when deployment friction slows the whole team. Expect $70 to $160 per hour by seniority.
What this role actually does
The clearest signal that you need this role is that shipping has become an event. Deploys are scheduled, they require a specific person, and something usually goes wrong. That friction compounds: engineers batch changes to avoid deploying, batches get riskier, and risk justifies more process.
A platform engineer inverts that. Infrastructure becomes code, environments become reproducible, deployment becomes automated and reversible, and production becomes observable enough that failures are diagnosed in minutes rather than hours. The measurable outcome is smaller, more frequent changes with lower failure rates.
Core skills to look for
- Kubernetes in production, including the parts that are genuinely painful
- Terraform or equivalent infrastructure as code, with real state discipline
- CI/CD pipeline design that is fast enough that people do not route around it
- Cloud platform depth, most commonly AWS
- Observability: metrics, logs, traces and alerts that mean something
- Incident response, on-call design and blameless post-mortems
- Security fundamentals: secrets management, least privilege, supply chain
When you need to hire this role
- Deploys are slow, manual or frightening
- Environments drift and 'works on staging' has stopped meaning anything
- Cloud spend is growing without a clear owner
- Incidents take hours to diagnose because nothing is instrumented
- Every engineer solves infrastructure problems differently
How to assess candidates for this role
Ask them to describe an outage end to end
Detection, diagnosis, mitigation, post-mortem. The structure of the answer reveals how mature their operational practice really is.
Probe infrastructure-as-code discipline
Ask how they handle state conflicts and drift. Anyone who has run Terraform at scale has strong opinions here.
Test pipeline thinking
Ask how they would take a 40-minute build to under 10. Expect caching, parallelism and dependency analysis.
Check the cost conversation
Ask how they would reduce cloud spend without reducing capacity. Look for rightsizing and utilisation data, not blanket cuts.
Typical rate bands
| Level | Experience | Typical rate | What they own |
|---|---|---|---|
| Mid-level | 3-5 years | $70-100/hr | Maintains pipelines and infrastructure within existing patterns |
| Senior | 6-9 years | $100-135/hr | Owns platform architecture, reliability and cost |
| Staff / Principal | 10+ years | $135-160/hr | Designs the internal developer platform and reliability strategy |
Frequently asked questions
What is the difference between DevOps and platform engineering?
DevOps is a practice — shared ownership of building and running software. Platform engineering is a role that builds internal tooling so product teams can do that safely. Most job postings labelled DevOps are describing platform engineering.
When do we need our first platform engineer?
Usually when deployment friction starts slowing every team, or when nobody owns reliability and incidents are diagnosed by whoever is available. Before that, a senior backend engineer can typically carry it part-time.
Do we really need Kubernetes?
Often not. Managed platforms cover many workloads with far less operational burden. A good candidate will ask about your scale and team size before recommending Kubernetes rather than assuming it.
How much does a platform engineer cost?
Typical vetted contract rates are $70 to $100 per hour at mid-level, $100 to $135 at senior and $135 to $160 for staff and principal, depending on infrastructure complexity and on-call expectations.
How do we measure whether platform work is paying off?
Deployment frequency, lead time from commit to production, change failure rate and time to restore. These four metrics are well established and hard to game without genuinely improving the system.