EPAM Systems
Editor's pick #1Global engineering firm with one of the largest certified AI benches available for hire
What is EPAM Systems?
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with roughly 61,000 employees across delivery centers in Europe, the Americas and Asia. It is a public company listed on the New York Stock Exchange. On its Q2 2026 earnings call, management said EPAM had more than 5,700 Anthropic-certified engineers and was among the five largest certified partners worldwide, with AI-native work making up about 11% of revenue. EPAM employs its engineers directly and sells them as augmented capacity, dedicated teams or managed programs, though most large accounts end up in the managed model.
EPAM Systems works primarily with clients in Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing sectors. Its primary differentiator is: Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes.
EPAM Systems tech stack and services
| Service area |
|---|
| LLM Engineers |
| AI Agent Developers |
| MLOps |
| Data Engineering |
| RAG & GenAI |
| Dedicated Teams |
| Eastern Europe Talent |
EPAM Systems pricing
Short answer: EPAM Systems uses a time and materials for augmented engineers; dedicated team and managed program contracts; rates on request pricing approach. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Full-time dedicated engineers | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Managed delivery | Variable; depends on team size | Large programmes or team augmentation |
EPAM Systems pros and cons
| Advantages | Things to consider |
|---|---|
| +A Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list | -Rates are among the highest on this list and are only shared after scoping |
| +Public-company reporting, audited financials and mature security reviews make vendor onboarding easier at banks and insurers | -Small requests for one or two engineers rarely get the same attention as large programs |
| +Can staff ten or more AI engineers in parallel across several time zones without running out of senior people | -Engagements tend to drift toward managed delivery, which moves decisions away from your own team |
| +Deep data-platform practice means LLM work and the data engineering under it can come from one supplier |
EPAM Systems vs alternatives
How EPAM Systems compares to the other top AI Staff Augmentation companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Turing | Fast access to LLM and ML specialists from... | An AI-first network whose engineers also do model training and evaluation work for frontier labs | 4.5 | Full comparison |
| Tensorway | Product teams adding senior AI specialists without vendor... | Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories | 4.4 | Full comparison |
| BairesDev | U.S. companies needing several AI engineers on matching... | A large salaried Latin American bench that works U.S. time zones | 4.3 | Full comparison |
| deepsense.ai | Research-heavy ML problems, computer vision, edge AI. | A pure applied-AI firm whose augmented engineers come from a research-grade data-science bench | 4.3 | Full comparison |
| N-iX | Data-heavy AI work needing a large European team. | Data engineering and ML from a 2,000-person European employer with two decades of delivery history | 4.2 | Full comparison |
| Andela | Enterprises building blended global teams with AI skills. | A marketplace that certifies engineers on AI skills before placement | 4.2 | Full comparison |
| Toptal | Short engagements with one senior AI specialist. | A heavily screened freelance pool that can supply one senior expert quickly | 4.2 | Full comparison |
| Globant | Enterprises wanting AI capacity on a subscription model. | Subscription-based AI Pods as an alternative to per-engineer billing | 4.1 | Full comparison |
| Azumo | Nearshore LLM and NLP builds for U.S. mid-market. | A nearshore team that also builds its own NLP products | 4.1 | Full comparison |
| InData Labs | Mid-sized companies adding data scientists to product teams. | A data-science-only firm small enough that senior staff stay involved | 4.1 | Full comparison |
| Innowise | Companies needing AI engineers plus surrounding app developers. | A large in-house bench that can staff AI and conventional engineering roles together | 4.1 | Full comparison |
| Uvik Software | Python-heavy AI teams wanting transparent pricing. | Published rate band, minimum term and replacement guarantee | 4.0 | Full comparison |
| DataArt | Finance and healthcare firms extending data and AI... | Nearly three decades of domain work in finance, healthcare and travel | 4.0 | Full comparison |
| Encora | U.S. firms wanting nearshore AI teams from a... | Large Mexican and Latin American delivery base with an AI engineering practice | 4.0 | Full comparison |
| Wizeline | U.S. companies wanting Mexico-based AI engineers. | A Guadalajara delivery base close to U.S. clients in time and travel | 4.0 | Full comparison |
| Intellias | Automotive and location-tech teams adding ML engineers. | Domain depth in automotive and mapping software | 4.0 | Full comparison |
| Kanerika | Microsoft Fabric and Databricks shops needing AI-ready data. | Platform specialists for Fabric, Databricks and Snowflake | 3.9 | Full comparison |
| Nearsure | U.S. teams adding Latin American GenAI developers. | Augmentation-first business model with a growing AI studio | 3.9 | Full comparison |
| nCube | Companies building a long-term offshore AI team. | Builds and runs a client-branded R&D team, including HR and office setup | 3.9 | Full comparison |
| Svitla Systems | Long-running team extension with mixed AI and app... | Two decades of team-extension relationships with U.S. clients | 3.9 | Full comparison |
| STX Next | Python codebases adding LLM and data engineers. | Python specialization applied to data and AI delivery | 3.9 | Full comparison |
| Howdy.com | U.S. startups hiring full-time Latin American AI engineers. | Full-time, single-client placements with employment handled by Howdy | 3.9 | Full comparison |
| Revelo | Hiring Latin American developers through a marketplace. | A very large Latin American pool with payroll and compliance included | 3.8 | Full comparison |
| BEON.tech | U.S. teams wanting Argentina-based data and ML engineers. | Nearshore recruitment focused on AI and data science roles | 3.8 | Full comparison |
| Xenoss | AdTech and MarTech firms needing real-time data plus... | Real-time, high-load data engineering from AdTech roots | 3.8 | Full comparison |
| Simform | Cloud-first companies adding AI and data engineers. | Cloud and data engineering paired with AI/ML from an India-based bench | 3.8 | Full comparison |
| Vention | Venture-backed startups scaling product and AI engineers. | Long record of extending startup engineering teams | 3.8 | Full comparison |
| ScienceSoft | Regulated companies wanting a documented hiring process. | Publishes its staff augmentation timeline and process | 3.7 | Full comparison |
| Mobilunity | Budget-conscious teams hiring one dedicated developer. | Lowest published rate band among the companies reviewed | 3.7 | Full comparison |
| Neoteric | Small GenAI pilots with a low entry cost. | Low $10,000 minimum for AI discovery and proof-of-concept work | 3.7 | Full comparison |
| LeewayHertz | Hackett Group clients adding GenAI developers. | GenAI app development backed by a public consulting parent | 3.6 | Full comparison |
EPAM Systems FAQ
What is EPAM Systems?
Global engineering firm with one of the largest certified AI benches available for hire
How much does EPAM Systems charge?
EPAM Systems uses time and materials for augmented engineers; dedicated team and managed program contracts; rates on request pricing. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does EPAM Systems use?
EPAM Systems works with Python, PyTorch, TensorFlow, LangChain, OpenAI, Anthropic Claude, AWS SageMaker, Azure ML, Databricks, Kubernetes. Primary industries served include Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing.
Is EPAM Systems right for enterprise?
Large enterprises, regulated industries, multi-team AI programs. 61,000+ team size. Key consideration: Rates are among the highest on this list and are only shared after scoping.
What are the best EPAM Systems alternatives?
The best alternatives to EPAM Systems depend on your use case. Top options are:
- Turing: an ai-first network whose engineers also do model training and evaluation work for frontier labs
- Tensorway: senior ai engineers run the technical screening, and every model and line of code stays in the client's repositories
- BairesDev: a large salaried latin american bench that works u.s. time zones
Compare EPAM Systems with other AI Staff Augmentation companies
Verify all details directly with EPAM Systems before making a decision.