EPAM AWS Forward Deployed Engineering (FDE)

Agentic AI in production, delivered by AWS-credentialed engineers inside your team.

Small pods of AWS-credentialed Forward Deployed Engineers work alongside your people and take agentic AI from a qualified opportunity to a measured result in production. We build on AWS, reuse a proven production harness, and agree the business outcome, the accuracy bar and the guardrails before the first line of code. Each engagement starts further ahead than the last.

Most agentic AI stalls between the demo and production. Our engineers ground the agents in your data and domain, measure them against test cases your experts own, and stay until the system runs in production and delivers the outcome you signed up for.

Agentic transformation. We go beyond assistants and dashboards to business processes that agents run end to end, with your people approving key decisions, and to customer-facing agents. On AWS, our pods build multi-agent systems on Amazon Bedrock and Amazon Bedrock AgentCore, ground them in your enterprise data and knowledge graphs, connect them through governed tools and the Model Context Protocol (MCP), and place human-in-the-loop checkpoints and Amazon Bedrock Guardrails around the decisions that matter.

AI-driven development lifecycle (AI-DLC). We build software with agentic developer tooling, from EPAM AI/Run to Kiro. Specifications, steering files and hooks become versioned, reusable assets, with quality gates on every change and human review before anything is merged. We measure the effect against your own pre-AI baseline, so each new team starts from a larger library of proven work.

Harness engineering. At the core is the harness: the reusable software that makes non-deterministic models behave as dependable production systems. EPAM builds, evaluates and operates it across twelve layers in three planes — the agent plane (execution, tooling, context and memory, orchestration, observability, verification, identity and trust, governance), the grounding plane (data integration, ontology and semantics) and the delivery plane (builder loop, compounding layer). It runs on AWS, with accuracy measured before and after every release.

Typical starting points, not a complete list of what we have delivered:

• Clinical and care workflows. Agents in the electronic medical record that prefill case details, draft documentation and summarize patient history, with clinicians reviewing every output.
• Sales and customer engagement. Multi-agent platforms that guide sellers from discovery to pricing, quotes and renewals across CRM, CPQ and ERP, with people approving commercial decisions.
• Data and analytics. A semantic layer over a knowledge graph for plain-language questions across policy, customer and operational data, with human approval gates for sensitive answers.
• Software delivery. AI-native engineering across many product teams: spec-driven development, agents for requirements, design reviews, tests and release notes.
• Operations and compliance. Agents that gather evidence, triage cases and prepare decisions in regulated processes such as KYC and KYB onboarding, where rules and people make the final call.

A constant pod runs four phases: Discover and ground (confirm use case, business case and success metrics; agree accuracy thresholds; ground the agents in your data); Build and orchestrate (build the agentic system with AI-DLC, with quality gates on every change); Prove and release (evaluate against ground-truth test cases co-owned with your experts, enforce controls, release only when the agreed bar is met — target 45 to 90 days to first production release); Operate and compound (hand over runbooks, dashboards and KPIs, keep measuring, and add reusable assets to the harness).

• AWS-credentialed FDE pods of two to six engineers covering data and integration, agent orchestration, and evaluation and governance — the same pod from discovery to production.
• A proven, reusable harness on EPAM AI/Run that can run in your own AWS account, validated through the AWS Customer-Deployed Foundational Technical Review.
• Built on AWS: Amazon Bedrock and AgentCore, Guardrails and Knowledge Bases, AWS Lambda and Amazon EKS, Amazon Neptune and Amazon DynamoDB, and AWS identity, encryption and audit services, in your account and Region.
• Security and governance by design: personal data masked, least-privilege agent identity, human decisions kept with humans, hard limits enforced outside the model, every action logged.

AWS Premier Tier Services Partner and 2025 AWS Global Innovation Partner of the Year. 6,000+ AWS-certified engineers and 1,000+ AWS projects delivered.