- React/Next.js Full-Stack: React, Next.js, TypeScript, Node.js
- Python/FastAPI Full-Stack: Python, FastAPI, React, PostgreSQL
- AI-Integrated Full-Stack: LLM API integration, RAG, End-to-end AI features
Hire
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ENGAGE WITHOUT BORDERS
Reach experienced engineers your usual recruiting channels miss.
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FILL CRITICAL ROLES
Access senior-level expertise immediately, without waiting out a full local hiring cycle.
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KEEP YOUR ROADMAP MOVING
Scale your team’s capacity on demand without the overhead of permanent headcount.
Keep Full Ownership
The Devox Software Staff Augmentation Model
Staff augmentation adds engineering capacity to a team you already have. Engineers work with your repositories, tooling, and review process, under Devox Software’s management. You manage priorities and acceptance. We handle sourcing, contracting, and everything that comes with the employment relationship.
Staff Augmentation vs. Dedicated Team
Our Staff Augmentation model is built for speed and flexibility, allowing you to quickly fill open seats month-to-month while conducting your own candidate interviews. In contrast, our Dedicated Team model offers full team-based ownership, end-to-end delivery management, and long-term continuity. For more details, visit our dedicated team page.
Global Engineering. A US Company on the Contract.
Your contract is with our US entity, providing you with legal clarity and consistency.
- Ownership Under US Copyright Law. Your MSA carries a present written assignment of copyright consistent with Section 204 of the US Copyright Act. Engineers sign an upstream assignment as a condition of repository access.
- The Employer Obligations Stay With Us. Payroll tax filings, statutory benefits, leave accrual, severance under local labor law, mandatory insurance coverage where the hub jurisdiction requires it, and entity registration in each hub remain Devox Software obligations. You pay a single vendor invoice.
Access and Security Controls
Engineers use your system access methods on Devox-managed devices. Access provisioning and revocation follow the process agreed in the engagement. Our most recent SOC 2 Type II report, including the in-scope criteria and the audit period, is available under NDA.
Why Devox Software
A Better Way to Add Engineering Capacity
First Candidates in 7 Business Days
Within 7 business days of agreeing on the role profile, we typically present 2–4 matched profiles. Timelines depend on the stack and seniority.
You Run the Interviews
Every candidate goes through your interview loop, and you decide who to bring on. Turning someone down costs only the time you invest in the interview process.
Your Code and Your IP, From Day One
Source code, architecture, and documentation are assigned to you under the MSA, effective from the first commit.
A Team Behind Every Engineer
An account manager and our delivery team back each engineer. When a tough problem comes up, the engineer can pull in colleagues who have solved similar ones before.
Scale and Adapt Your Model
Begin with a single engineer and evolve your engagement model—from Staff Augmentation to a Dedicated Team—as your project scope and requirements change.
Engineers We Recruit For
Engineers We Recruit For
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Full-Stack Engineers
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Software Engineers (AI-assisted)
- AI-Assisted Software Engineer: Cursor, Claude Code, GitHub Copilot, AI code generation, Prompt-driven development
- Legacy Modernization Engineer: AI-assisted code modernization, Legacy system refactoring, Codebase analysis with AI, Automated code translation, Technical debt reduction
- Migration Engineer: Zero-downtime migrations, Incremental system migration, Data migration strategies, Blue-green deployments, Cutover planning
- Full-Stack AI Delivery Engineer: End-to-end AI-powered delivery, Rapid prototyping with AI tools, AI-assisted testing, Production-ready AI workflows, Cross-stack implementation
- Modernization Architect: System redesign for the AI era, Architecture for legacy replacement, Risk assessment in migrations, Hybrid legacy-modern systems, Long-term modernization roadmaps
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Applied AI Engineering
- Production LLM / RAG Engineers: LangChain / LlamaIndex, Vector DBs (Pinecone, Weaviate, pgvector), Hybrid retrieval, Evaluation harnesses, Cost-aware serving
- Agentic AI Engineers: LangGraph, Multi-agent orchestration, Tool-use, Memory, Reliability & guardrails, Observability
- Forward Deployed / Applied AI Engineers: Enterprise integration, Rapid productionization, Client-facing delivery, Legacy systems + AI, Solution prototyping
- Production ML Engineers: PyTorch, Model training + deployment, Hybrid classical + LLM systems, Data pipelines for AI, Fine-tuning
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AI Infrastructure & MLOps
- AI Platform Engineer: Internal AI infrastructure, Model training platforms, GPU cluster management, Feature stores, Developer experience for ML teams
- Model Serving Engineer: Model serving, Inference optimization, vLLM, Triton Inference Server, Latency and throughput tuning
- MLOps Engineer: MLOps pipelines, CI/CD for models, Model registry, Experiment tracking, Production model deployment
- ML Observability Engineer: Model monitoring, Drift detection, Performance observability, Alerting for production models, Data quality monitoring
- LLMOps Engineer: LLM serving infrastructure, Prompt caching, Cost control for inference, LLM evaluation pipelines, Agent runtime management
- Infrastructure Engineer for AI: Kubernetes for AI workloads, GPU scheduling, Containerization for models, Cloud AI platforms, Cost optimization
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AI Security Engineers
- AI Governance Specialist: NIST AI Risk Management Framework, Model risk assessment, AI policy development, SOC 2 for AI, Regulatory compliance mapping
- AI Red Team Specialist: Adversarial testing, Threat modeling, Vulnerability analysis, Penetration testing, Security controls assessment
- Secure AI Platform Engineer: MLOps security controls, Model serving security, Agent isolation, AI system observability, Model supply chain security
- AI Application Security Engineer: Secure coding for LLM applications, Input/output validation, Guardrails design, RAG security, Tool use restrictions
- AI Data Engineer: AI-ready data pipelines, Embedding generation pipelines, Vector database pipelines, Feature store development, Training data pipelines
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Data Platform Engineers
- Analytics Engineer: Dbt modeling, Semantic layer, Metric layer, Tested transformations, Business logic in SQL
- Data Governance Engineer: Column-level lineage, Data quality monitoring, Data contracts, Access policies, Governance frameworks
- Pipeline Engineer: Apache Airflow, Reliable data pipelines, ETL ELT design, Orchestration, Pipeline monitoring
- Streaming Data Engineer: Real-time pipelines, Kafka, Flink, Event-driven architecture, Streaming SQL
- DataOps Engineer: CI/CD for data, Data observability, Infrastructure as code, Pipeline reliability, Automated testing
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Cloud / DevOps Engineers
- Platform Engineer: Internal developer platforms, Kubernetes, Terraform, Self-service infrastructure, Developer experience
- Site Reliability Engineer: Reliability engineering, SLOs and error budgets, Observability, Incident response, Production system health
- Kubernetes Engineer: Kubernetes, GPU scheduling, Helm, Cluster management, AI workload orchestration
- Cloud Infrastructure Engineer: AWS, Scalable cloud architecture, Cost optimization, Infrastructure as code, High availability
- DevOps Engineer: CI/CD pipelines, Automation, Docker, Terraform, Cloud platforms
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Quality Engineering
- Playwright Automation Engineer: Playwright, TypeScript, End-to-end testing, CI/CD integration, Cross-browser automation
- AI Test Engineer: LLM evaluation, AI agent testing, Hallucination detection, Prompt testing, AI-powered test generation
- Selenium Automation Engineer: Selenium, Java, Test frameworks, Regression automation, WebDriver
- SDET: Software development in test, Test framework design, API testing, CI/CD pipelines, Code-level quality
- API Automation Engineer: API testing, Postman, REST validation, Contract testing, Backend quality gates
- AI-Augmented QA Engineer: Self-healing tests, AI test generation, Quality gates, Continuous testing, AI tools in QA workflows
When to Use This Model
Best-Fit Scenarios
- Your roadmap has approval, and the work waits on an open role. The budget exists, and the delivery date keeps moving further out each week the seat stays empty.
- The role has stayed open for months on a thin shortlist. The stack, the seniority, or the location made it harder to fill than the plan assumed.
- A migration or a compliance deadline calls for expertise your team will need only once. Six months of specialist work rarely justifies a permanent seat.
- Your engineers spend their weeks on maintenance while product work waits. Adding capacity frees the people who already hold the system context.
- Headcount is frozen, and delivery expectations stay where they were. You add engineering capacity through a vendor invoice.
Specialized Domain Experience
Solving Complex Industry Challenges
01
Manufacturing & Industrial Systems
MES, SCADA, production control, predictive maintenance, shop-floor AI.
02
Automotive
SDV architecture, digital twins, OTA platforms, embedded + cloud systems.
03
Logistics and Supply Chain
TMS/WMS modernization, real-time optimization, multi-system integration.
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Legacy Enterprise Modernization
Long-lived monoliths, zero-downtime migration, regulated environments.
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AI-Native Platform Engineering
Production LLM/RAG systems, agentic workflows, internal AI platforms with governance.
06
Financial Infrastructure & Payments
Core banking layers, payment processing, compliance-heavy transaction systems.
07
Energy & Utilities Operations
Grid management, asset monitoring, predictive operations, OT/IT convergence.
08
Complex Product Platforms
Multi-tenant SaaS with heavy technical debt, high-availability requirements, continuous evolution.
AI & ML
AI-Powered Platform for Short-Term Personal Property Insurance
An AI-powered app set out to test a new product for short-term personal property insurance, starting from as little as one day of coverage.
Additional Info
Core Tech:
- Python
- Django
- Flask
- JavaScript
- PostgreSQL
- AWS (EC2, S3)
- ELK Stack
Country:
USA
AI & ML
Optimizing Migrations: Neural Networks for Column Classification and Anomaly Detection for a Tech Startup
Advanced machine learning techniques streamline data table processing as part of an end-to-end product. Neural networks identify data types, detect anomalies, and classify columns for a smooth automated migration. Real-time. Accurate. Fast.
Additional Info
Core Tech:
- Python
- Keras
- Pandas library
- Scikit-learn
- NLTK (Natural Language Toolkit)
Country:
USA
Testimonials
Testimonials
Sweden
The solutions they’re providing is helping our business run more smoothly. We’ve been able to make quick developments with them, meeting our product vision within the timeline we set up. Listen to them because they can give strong advice about how to build good products.
Carl-Fredrik Linné
Tech Lead at
CURE Media
United States
We are a software startup and using Devox allowed us to get an MVP to market faster and less cost than trying to build and fund an R&D team initially. Communication was excellent with Devox. This is a top notch firm.
Darrin Lipscomb
CEO, Founder at
Ferretly
Australia
Their level of understanding, detail, and work ethic was great. We had 2 designers, 2 developers, PM and QA specialist. I am extremely satisfied with the end deliverables. Devox Software was always on time during the process.
Daniel Bertuccio
Marketing Manager at
Eurolinx
Australia
We get great satisfaction working with them. They help us produce a product we’re happy with as co-founders. The feedback we got from customers was really great, too. Customers get what we do and we feel like we’re really reaching our target market.
Trent Allan
CTO, Co-founder at
Active Place
United Kingdom
I’m blown up with the level of professionalism that’s been shown, as well as the welcoming nature and the social aspects. Devox Software is really on the ball technically.
Andy Morrey
Managing Director at Magma Trading
Switzerland
Great job! We met the deadlines and brought happiness to our customers. Communication was perfect. Quick response. No problems with anything during the project. Their experienced team and perfect communication offer the best mix of quality and rates.
Vadim Ivanenko
COO at
Optherium
United States
The project continues to be a success. As an early-stage company, we're continuously iterating to find product success. Devox has been quick and effective at iterating alongside us. I'm happy with the team, their responsiveness, and their output.
Sweden
We hired the Devox team for a complicated (unusual interaction) UX/UI assignment. The team managed the project well both for initial time estimates and also weekly follow-ups throughout delivery. Overall, efficient work with a nice professional team.
John Boman
Product Manager at
Lexplore
Canada
Their intuition about the product and their willingness to try new approaches and show them to our team as alternatives to our set course were impressive. The Devox team makes it incredibly easy to work with, and their ability to manage our team and set expectations was outstanding.
Tamas Pataky
Head of Product at
Stromcore
Estonia
Devox is a team of exepctional talent and responsible executives. All of the talent we outstaffed from the company were experts in their fields and delivered quality work. They also take full ownership to what they deliver to you. If you work with Devox you will get actual results and you can rest assured that the result will procude value.
Stan Sadokov
Product Lead at
Multilogin
United Kingdom
The work that the team has done on our project has been nothing short of incredible – it has surpassed all expectations I had and really is something I could only have dreamt of finding. Team is hard working, dedicated, personable and passionate. I have worked with people literally all over the world both in business and as freelancer, and people from Devox Software are 1 in a million.
Mark Lamb
Technical Director at M3 Network Limited
Insights
Our Experts' Insights
Custom Software Development
Industry Trends
Top IT Staff Augmentation Companies in 2026
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Outsourcing
Software Development
Startups
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Custom Software Development
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FAQ
Frequently Asked Questions
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Who manages the engineers day-to-day?
You set priorities, review deliverables, and accept the work. Devox Software directs how the work is performed, while managing payroll, performance, and equipment.
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Do you have experience in my industry?
Yes. We recruit engineers who have already worked in these domains and understand their specifics: regulatory requirements, data sensitivity, complex integrations, and the legacy systems often found there. They leverage their existing domain expertise to quickly grasp your business context and navigate common industry pitfalls from day one.
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How do you ensure project success and fit?
At kickoff, we agree with you on what counts as success in the first weeks and months: delivery pace, code quality, how smoothly the person joins the team, and the specific deliverables. We return to those criteria and collect feedback against them, so you can always see whether the engagement is moving in the right direction.
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How do your engineers adapt to our timezone and tools?
Most of our engineers keep a schedule that substantially overlaps with US Eastern and Central time. They are already used to working in Slack, Jira, GitHub, Linear, Notion, and quickly adjust to your internal processes and rituals. Onboarding into tools and communication usually takes just a few days, not weeks.
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How do you manage AI security and compliance?
We can provide you with a dedicated Cybersecurity & AI Governance engineer, as well as a team comprising an AI Engineer and a Security Specialist. They work with the engineering team early, so security controls are part of the design. This matters most in regulated industries, where security and governance requirements can’t be bolted on after launch.
We can provide you with a dedicated Cybersecurity & AI Governance engineer, as well as a team comprising an AI Engineer and a Security Specialist. They work with the engineering team early, so security controls are part of the design. This matters most in regulated industries, where security and governance requirements can’t be bolted on after launch.
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Do your AI engineers have real-world production experience?
Yes. We screen for production experience. The engineers we offer have already built and deployed RAG systems, multi-agent workflows, evaluation harnesses, and cost/latency control mechanisms to production. They know how a model behaves under real load, where hallucinations arise, how to set up guardrails, and what to do when something goes wrong at two in the morning.
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How do you ensure long-term retention and quality?
Retention matters because replacing an engineer after onboarding is expensive and disruptive. Therefore, we provide dedicated, ongoing support to ensure every engineer integrates seamlessly and performs at their best. Each engineer has an internal tech lead who helps with onboarding, resolves complex technical issues, and ensures the person feels supported. We also screen for engineers who commit to long-term engagements.
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Do you have experience with legacy system modernization?
Yes. Legacy modernization is one of our core areas of experience. Most of the engineers we offer have years of experience specifically with legacy, poorly documented code, tangled dependencies, old frameworks, and the requirement that business continues to work during changes. They modernize systems incrementally, ensuring business continuity throughout the transition.
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