4.9/5 on Clutch — 13 verified reviews

Hire DevOps Engineers

When deployments stall and cloud bills climb, teams hire DevOps engineers to steady the pipeline. Kodexo Labs places production-vetted engineers through staff augmentation, backed by the same AI-native work behind Diesel Laptops, where technicians find answers 85% faster, and Extensiv.

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TRUSTED BY ENTERPRISES

Every engineer Kodexo Labs places has shipped infrastructure that runs in production, not just passed an interview. Here are the six areas a dedicated DevOps hire covers for your team from day one:

What a dedicated DevOps hire covers:

  • CI/CD pipelines that ship code faster with fewer failed releases

  • Kubernetes clusters that scale under heavy load without any downtime

  • Infrastructure-as-code that makes environments repeatable, auditable, and fast to rebuild

  • Cloud cost engineering that shows where spend goes, cutting waste

  • MLOps that puts AI models into production, reliably and repeatably

  • Observability that catches incidents early and protects uptime customers expect

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Hire DevOps Engineers
94%

client retention rate across ongoing client engagements

Top-Rated

AI Development Company · Verified on Clutch

51

AI-powered products shipped across 25+ industries

PhD-Level

expert team across US, UK, Pakistan, and Canada

Hire DevOps Engineers Across Seven Specialisms

DevOps staff augmentation works when the engineer has done the job before. Whether you need a lead DevOps engineer or an offshore DevOps engineer, each specialism below maps to real production work Kodexo Labs has shipped.

CI/CD Pipeline Engineering

Your releases keep breaking at the worst time. A CI/CD engineer automates the build, test, and deploy steps so code ships without surprises.

Automated build and test pipelines

Every commit is built and tested on its own, so a break shows fast.

Faster and more predictable release cadence

Teams ship several times a day, not once a month, with far less risk.

See What Kodexo Labs Engineers Ship in Production

The same team behind Diesel Laptops, Extensiv's 90%+ accuracy, and a 94% client retention rate can extend yours with a proven DevOps engineer.

Shipped, Measured, Still Running

Diesel Laptops

Fleet technicians lost minutes on every job hunting through 160,000 parts records. Solution: Kodexo Labs built an AI parts-lookup running inside their own self-hosted AWS VPC, keeping all data on their private cloud. Outcome: lookup time fell 85%, so a technician finds the right part in seconds, not minutes, on every daily job.

85%

Faster Lookup

160,000

Records Searched

Inc. 5000

Client

Diesel Laptop

Extensiv

This $130M-funded logistics platform had operations staff waiting on engineers for every data question spread across 4 databases. Solution: Kodexo Labs built a LangGraph agentic system that reads plain-English questions and answers them directly. Outcome: staff now query 207 tables themselves, at over 90% accuracy, with answers arriving in seconds instead of days.

90%+

Accuracy

207

Tables

$130M+

Funded (Hg Capital)

Extensiv

SmartMedHx

Clinicians were losing visit time to manual note-taking during patient appointments. Solution: Kodexo Labs built HIPAA-compliant, patent-pending documentation AI that captures the conversation and writes the notes automatically, keeping patient data protected. Outcome: 42 providers now document visits hands-free, 493 patient interviews processed, and the client returned for a second, separate legal-tech build.

42

Providers

493

Interviews Processed

HIPAA

Compliant From Day One

DRAG

What Clients Say About The Team

Fast-growing organisations do not applaud a consulting partner for polished slide presentations; they praise it for showing up when something actually breaks. The notes below come from founders who watched Kodexo Labs work the problem in real time.

Kodexo Labs has met all expectations; the team delivers on time and manages the project seamlessly. They respond promptly to needs and communicate effectively through virtual meetings, Google Chat, and WhatsApp. Overall, they're highly passionate about the project and excel in customer service.

Christopher Brigham

MD President, Brigham and Associates, Inc.

WATCH VIDEO

  • HIPAA-compliant CI/CD pipelines
    Audit-trail logging built-in
    Clinical-tool uptime engineering
    PHI-safe cloud environments

DevOps Infrastructure Built for the Realities of Eight Industries

Infrastructure needs shift by sector. A hospital cares about audit trails; a warehouse cares about throughput under load. Each tab shows how our DevOps hiring narrows to the reliability and compliance pressures your specific industry actually faces.

Put Kodexo Labs DevOps Engineers Behind Your Next Production Release

The same team behind 51 shipped products and a 94% client retention rate can scope your infrastructure, vet the right engineers, and have them building inside your stack within a matter of weeks.

HIPAA, SOC 2, and AWS VPC Isolation by Default

Compliance is architected into the pipeline, not bolted on after an audit. SmartMedHx runs clinical documentation on HIPAA-compliant infrastructure our team built and operates. Every engagement inherits the same posture: SOC 2 controls, GDPR data handling, PCI-DSS environments, AWS VPC isolation, and audit-trail logging.

hipaa-logo

HIPAA

SOC TYPE 2 Logo

SOC TYPE 2

gdpr-compliance

GDPR

PCI-DSS

PCI-DSS

iso-27001

ISO 27001

ccpa-compliance

CCPA

COPPA Logo

COPPA

EU AI Act Logo

EU AI Act

NIST AI RMF Logo

NIST AI RMF

FERPA Logo

FERPA

hipaa-logo

HIPAA

SOC TYPE 2 Logo

SOC TYPE 2

gdpr-compliance

GDPR

PCI-DSS

PCI-DSS

iso-27001

ISO 27001

ccpa-compliance

CCPA

COPPA Logo

COPPA

EU AI Act Logo

EU AI Act

NIST AI RMF Logo

NIST AI RMF

FERPA Logo

FERPA

What Separates Kodexo Labs DevOps Engineers From a Generic Staffing Bench: Shipped Infrastructure

Most staffing vendors hand you a resume and wish you luck. We hand you engineers who have already built and run production infrastructure for Inc. 5000 companies. Here is what that looks like in practice.

Production-Grade Tool Integration, Not Prototypes

Production-grade CI/CD, day one

Zendrop was stuck in a slow, costly launch cycle. Our team rebuilt the pipeline, cut time to market by 45% and launch costs by 50%, and lifted conversion 25% under real release load.

Cloud and AI Infrastructure icon

Your own sovereign cloud

Shared hosting risks a breach. We give you your own AWS VPC, private subnets, code-managed IAM roles, and encrypted storage as the baseline, not an upsell, across all 51 products we have shipped.

Compliance wired into pipelines

Therapy Talk had to pass an EU privacy audit before launch, not after. Our team wired GDPR data handling and access control into the pipeline itself, and it now serves 1,923 users today.

Depth across seven specialisms

Depth across seven specialisms

A bad hire stalls your roadmap for a quarter. Our practice spans seven infrastructure areas, from CI/CD and Kubernetes to FinOps and MLOps, and it traces back to 51 products across 25+ industries.

Ready to Scale Your AI Infrastructure Reliably

Shipping models is easy; keeping them reliable, observable, and affordable in production is where most teams stall. Our engineers build the pipelines, autoscaling, and monitoring that keep AI workloads dependable long after the first production launch.

Extensiv's operations team now queries its own data in plain English, the same LangGraph rigor we staff for your production MLOps infrastructure.

Recognised By The Platforms That Vet AI Companies

Kodexo Labs is reviewed where technical buyers do their diligence: Clutch and Upwork. Every badge below links to the live profile.

Top Clutch Artificial Intelligence Company 2024 Award
Top Clutch Machine Learning Company San Francisco 2026
Top Artificial Intelligence Company
Top Artificial Intelligence Companies 2022 by TopAppFirms
Top AI Development Company by Selected Firms
Top Clutch Chatbot Company 2024 Award
Clutch Spring Champion 2024
Upwork Top 1% · Top Rated
Top Clutch Health Wellness App Developers Chicago 2026
Top Clutch Generative Ai Company 2024 Award
Top Clutch Artificial Intelligence Company Chicago 2026
Top Clutch Artificial Intelligence Company 2024 Award
Top Clutch Machine Learning Company San Francisco 2026
Top Artificial Intelligence Company
Top Artificial Intelligence Companies 2022 by TopAppFirms
Top AI Development Company by Selected Firms
Top Clutch Chatbot Company 2024 Award
Clutch Spring Champion 2024
Upwork Top 1% · Top Rated
Top Clutch Health Wellness App Developers Chicago 2026
Top Clutch Generative Ai Company 2024 Award
Top Clutch Artificial Intelligence Company Chicago 2026

Overcoming DevOps Hiring and Delivery Challenges

Adding DevOps capacity fails quietly when releases stall, cloud bills climb, or incidents pile up faster than your team resolves them. Kodexo Labs places production-vetted engineers, drawn from the bench behind 51 shipped products, who close these gaps with automation, observability, and cost discipline built into every sprint.

Problem

Slow, Fragile Release Pipelines

Manual, inconsistent deployments turn every release into a gamble, and one failed rollout stalls shipping while engineers scramble to trace what broke.

Solution

  • Automated CI/CD pipelines replace manual steps, so releases ship the same predictable way.

  • GitOps rollback controls let teams reverse a bad deployment in minutes, not hours.

  • Progressive delivery and canary releases catch failures before they reach every production user.

Problem

Runaway Cloud Cost Sprawl

Cloud spend creeps upward as idle resources and oversized clusters accumulate, and finance cannot tell which team or service drives the bill.

Solution

  • FinOps tagging and live dashboards expose spend by team, service, and environment continuously.

  • Right-sized Kubernetes autoscaling matches compute to real demand and eliminates idle capacity waste.

  • CI/CD cost gates flag expensive infrastructure changes before they merge and reach production.

Problem

AI Workloads Outgrow Infrastructure

Teams ship AI features onto pipelines never built for models, so deployments break, GPU costs surprise finance, and monitoring misses accuracy drift.

Solution

  • MLOps pipelines version models, automate deployment, and monitor accuracy so drift surfaces early.

  • GPU autoscaling and FinOps tracking keep AI infrastructure costs predictable under variable load.

  • Extended CI/CD pipelines test and promote model changes with the same production rigor.

Problem

Slow, Fragile Release Pipelines

Manual, inconsistent deployments turn every release into a gamble, and one failed rollout stalls shipping while engineers scramble to trace what broke.

Solution

  • Automated CI/CD pipelines replace manual steps, so releases ship the same predictable way.

  • GitOps rollback controls let teams reverse a bad deployment in minutes, not hours.

  • Progressive delivery and canary releases catch failures before they reach every production user.

Problem

Slow, Fragile Release Pipelines

Manual, inconsistent deployments turn every release into a gamble, and one failed rollout stalls shipping while engineers scramble to trace what broke.

Solution

  • Automated CI/CD pipelines replace manual steps, so releases ship the same predictable way.

  • GitOps rollback controls let teams reverse a bad deployment in minutes, not hours.

  • Progressive delivery and canary releases catch failures before they reach every production user.

Problem

Runaway Cloud Cost Sprawl

Cloud spend creeps upward as idle resources and oversized clusters accumulate, and finance cannot tell which team or service drives the bill.

Solution

  • FinOps tagging and live dashboards expose spend by team, service, and environment continuously.

  • Right-sized Kubernetes autoscaling matches compute to real demand and eliminates idle capacity waste.

  • CI/CD cost gates flag expensive infrastructure changes before they merge and reach production.

Problem

AI Workloads Outgrow Infrastructure

Teams ship AI features onto pipelines never built for models, so deployments break, GPU costs surprise finance, and monitoring misses accuracy drift.

Solution

  • MLOps pipelines version models, automate deployment, and monitor accuracy so drift surfaces early.

  • GPU autoscaling and FinOps tracking keep AI infrastructure costs predictable under variable load.

  • Extended CI/CD pipelines test and promote model changes with the same production rigor.

Problem

Slow, Fragile Release Pipelines

Manual, inconsistent deployments turn every release into a gamble, and one failed rollout stalls shipping while engineers scramble to trace what broke.

Solution

  • Automated CI/CD pipelines replace manual steps, so releases ship the same predictable way.

  • GitOps rollback controls let teams reverse a bad deployment in minutes, not hours.

  • Progressive delivery and canary releases catch failures before they reach every production user.

Every tool listed is in active production on a Kodexo Labs.

Every framework, runtime, and cloud service named here is running on a live client product right now. No theoretical stack, no resume keywords, no tools added for marketing weight.

Python
Python

How to Hire a DevOps Engineer, Step-by-Step

From the first scoping call to steady delivery, here is how Kodexo Labs places a production-vetted engineer inside your team quickly.

1

Scope and Audit

Your role, cloud stack, and compliance needs get mapped in one working session, so the shortlist arrives matched to reality. This upfront DevOps consulting services step removes the costly rework that stalls most hires.

2

Vetting and Shortlist

Candidates reach your shortlist only after a production-style evaluation, not a resume screen. Every engineer we forward has already shipped and operated real infrastructure in a comparable cloud environment before you ever interview them.

Design & Prototyping
3

Client Technical Evaluation

You interview three to five pre-vetted engineers through async take-homes or live pairing sessions, with a Kodexo Labs engineering lead on the call whenever a deeper technical judgment is needed. The choice stays yours.

Development and Integration
4

Onboarding and Access

An onboarding sprint provisions cloud access, repository permissions, and tooling on day one, then ramps your engineer through the codebase, standups, and Jira so contribution starts in the first week, not the first month.

5

Delivery and Governance

From there, your engineer runs a steady sprint cadence with weekly demos, performance reviews, and ongoing governance across cost, reliability, and security, so FinOps discipline and observability stay part of the delivery, not an afterthought, the same discipline behind a 94% client retention rate.

Related Insights

IT Staffing Agencies – Kodexo Labs can Help Businesses Acquire Best Augmentation Solutions

July 2024 · By Kodexo Labs

What IT staffing agencies do and how to pick one: staff augmentation, team extension, outsourcing, cost, and a 7-step guide to choosing the right partner.

What is MLOps?

January 2024 · By Kodexo Labs

What MLOps is and how it works, covering MLOps vs DevOps, key components, tools, platforms, the MLOps engineer role, and leading MLOps companies.

What is LLMOps? How to be Efficient in Business Optimization

January 2024 · By Kodexo Labs

What LLMOps is and how it optimizes large language model operations, covering open-source LLMs, architecture, tools, and generative AI vs LLMs.

Frequently Asked Questions

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Still not sure what your team needs?

Book a Discovery Call

You are scoped by role, stack, and scope of work, not by an hourly rate. After a scoping call, we shape the engagement around your infrastructure goals and required seniority, then place a dedicated, contract-to-hire, or part-time engineer to match. For exact commercials, talk to our team directly.