Forward Deployed AI Architect

EPAM Systems; Washington (District of Columbia); Remote; USD 170,000 - 230,000; Full time

Benefits offered by this job

Medical, Dental and Vision Insurance (

Health Savings Account

Flexible Spending Accounts (Healthcare

Short-Term and Long-Term Disability

Life and AD&D Insurance

Employee Assistance Program

LinkedIn learning solutions

401(k) Matching

Paid Time Off 15-25 days

Paid Holidays 9 per year

Employee Discounts

Stock Purchase Program

Job summary

EPAM Systems seeks a Forward Deployed AI Architect to embed with client business and engineering teams, shaping AI-native solutions from pilot to production. You will own architecture, risk assessment, and governance across orchestration, retrieval, and system integration at enterprise scale.

You will operate at the client table, balancing business scope, technical trade-offs, and security controls, while driving measurable outcomes and repeatable patterns across engagements.

Qualifications

• Experience taking AI-native systems to production at a client in a consulting context.
• Proven client-facing architect with problem framing and decision-making.
• Strong integration, distributed, cloud, and data-flow architecture experience.
• Ability to work with ambiguity and map requirements to explicit decisions.
• Hands-on coding ability to prototype and validate constraints.

Responsibilities

• Embed with a client account, working directly with business owners, product leaders, engineering teams, security, risk, and operations to take AI solutions from pilot to production
• Design end-to-end AI-native architectures: orchestration, retrieval, integration with systems of record, agent autonomy and guardrails, identity and authorization, evaluation, observability, and cost model
• Own three artifacts that make your impact measurable: a capability economics model, trust-rung evidence for every agent, a knowledge-graph slice of the client domain
• Turn contradictory or incomplete requirements into explicit business decisions with named owners
• Decide, per component and per risk, how much can be delegated to AI and where a human must stay in the loop
• Define how each system is evaluated: fit to business scope, not just fluent output
• Build proofs of concept and reference implementations when needed
• Feed learnings back into EPAM's AI architecture practice: patterns, references, and best practices

Skills

AI architecture

Client-facing

Cloud architecture

ADR documentation

Travel readiness

Hands-on coding

Tools

APIs integration

Job description

Most enterprise AI initiatives stall between pilot and production. The demo works; the path to a system that runs a real business process, under real controls, with a real owner, is where they get stuck. The Forward Deployed AI Architect is the person we place inside the client to get them unstuck.

You will be embedded with client business owners and engineering leaders, designing AI-native, Enterprise AI and Applied AI solutions — assistants, RAG systems, agents, agentic workflows, autonomous components — and taking them from pilot to production. You will carry the architect's responsibilities (framing the problem, fitting the business scope exactly, making trade-offs explicit, deciding what the system must not do) while sitting at the client's table, in their vocabulary, on their timeline.

The role is modeled on the forward-deployed engineering pattern but operates at the architecture level. It rewards people who like ownership, who can work with ambiguity without a home team beside them, and who measure themselves by what reached production at the client, not by what was presented.

Req# 1090267686

Responsibilities

• Embed with a client account, working directly with business owners, product leaders, engineering teams, security, risk, and operations to take AI solutions from pilot to production
• Design end-to-end AI-native architectures: orchestration, retrieval, integration with systems of record, agent autonomy and guardrails, identity and authorization, evaluation, observability, and cost model
• Own three artifacts that make your impact measurable: a capability economics model — what each AI capability costs and what it earns, so investment decisions are made on evidence; trust-rung evidence for every agent — the documented proof of how much autonomy each agent has earned and under what controls; a knowledge-graph slice of the client domain — the entities, relationships, and constraints the solution depends on, captured so the architecture and the business share one model
• Turn contradictory or incomplete requirements into explicit business decisions with named owners
• Decide, per component and per risk, how much can be delegated to AI — including AI coding agents in the delivery process — and where a human must stay in the loop
• Define how each system is evaluated: how the client will know an assistant or agent fits the business scope, not just that it produces fluent output
• Build proofs of concept and reference implementations when a decision needs evidence or a team needs an example of "good"
• Feed what you learn at the client back into EPAM's AI architecture practice: patterns, reference architectures, and what generation gets wrong

Requirements

• You have taken AI-native systems to production at a client or customer — RAG, assistants, agents or agentic workflows with real users and real business processes behind them — in a solutions architecture, customer engineering, forward-deployed, or consulting role, with architect-level responsibility for the system around the model
• You are a proven solution architect from a consulting or client-facing background who has started building with AI on your own initiative in the last year or so, and wants to make AI-native design at the client's side the center of your work
• A track record of client- or customer-facing architecture: you have framed problems for people who are not technologists, presented options with costs and risks, and got decisions made
• Solid solution or software architecture experience with delivery accountability — systems you designed that shipped and ran
• Depth in integration, distributed systems, cloud, and data-flow architecture at enterprise scale
• Comfort operating with ambiguity, conflicting stakeholders, and shifting requirements, without waiting for clarity before starting
• A habit of writing things down so decisions survive you: ADRs, design documents, evidence for autonomy and risk decisions
• Recent hands-on coding ability, enough to prototype and keep your constraints honest
• Willingness to be on-site with clients and to travel as the engagement requires

Nice to have

• Regulated-industry experience — financial services, healthcare and life sciences, insurance — including working with security, risk, and compliance functions
• Agent frameworks, tool and function calling, MCP, orchestration patterns, LLM observability
• Identity and authorization for agentic systems (OAuth 2.1, SPIFFE, AuthZEN, DPoP)
• Experience with cost and token economics, or with building business cases for AI capabilities
• Presales, proposal, or account-shaping experience
• Forward-deployed or field engineering background at an AI or data platform vendor

We offer

• Medical, Dental and Vision Insurance (Subsidized)
• Health Savings Account
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Short-Term and Long-Term Disability (Company Provided)
• Life and AD&D Insurance (Company Provided)
• Employee Assistance Program
• Unlimited access to LinkedIn learning solutions
• Matched 401(k) Retirement Savings Plan
• Paid Time Off - the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)
• Paid Holidays - nine (9) total per year
• Legal Plan and Identity Theft ProtectionAccident Insurance
• Employee Discounts
• Pet Insurance
• Employee Stock Purchase Program
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program

This Remote Position Cannot be Performed in New York City.

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

Engineer the Future with a Career at EPAM

This posting includes a good faith range of the salary EPAM would reasonably expect to pay the selected candidate. The range provided reflects base salary only. Individual compensation offers within the range are based on a variety of factors, including, but not limited to: geographic location, experience, credentials, education, training; the demand for the role; and overall business and labor market considerations. Most candidates are hired at a salary within the range disclosed. Salary range: $170,000 - $230,000. In addition, the details highlighted in this job posting above are a general description of all other expected benefits and compensation for the position.

Applications will be accepted on a rolling basis.

In accordance with the LA County Fair Chance Ordinance, you may find a copy of the Notice containing a summary of the Ordinance’s key provisions here: Concept FCO Posting 8 27 24 (lacounty.gov)

EPAM will not provide new H-1B visa sponsorship for this position. Candidates with existing transferable H-1B status may be considered.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.