AI Solution Architect

We're seeking an AI Solution Architect to come aboard our team. This opportunity suits someone who takes satisfaction in walking teams through the hands-on challenges of constructing and verifying AI-powered systems. You'll collaborate closely with technical specialists and business-side stakeholders alike, helping connect cutting-edge AI potential with practical, applied outcomes. For those energized by a mix of experimental work and structured advisory contributions, this role presents a genuine chance to add real value.

Responsibilities Offer hands-on direction regarding agent development, covering model and tool choices, deployment tactics, evaluation approaches, and continuous monitoring Assess RAG/GraphRAG options, chunking methods, retrieval techniques, re-ranking strategies, and vector-store alternatives together with the architect, moving forward only with the approach agreed upon in the validation plan Establish golden datasets, define quality benchmarks, and build regression tests relying on sanctioned, controlled test data free of personal information Construct the approved nonproduction agent workflow using Python whenever bandwidth and readiness allow, covering its tools and a single API or system integration point Verify success scenarios, error conditions, and permission-related cases, capturing details on quality, cost of usage, known limitations, and outstanding gaps Put together a blueprint for workflow deployment and reuse alongside engineering playbooks, addressing semantic/context management, identity handling, permission structures, and autonomy boundaries Break down AI-assisted development methods and agent tooling choices in terms accessible to business users, engineering staff, and the AI team Create documented examples and facilitate walkthrough sessions, with advisory scope extending to production-grade lifecycle guidance, excluding actual production rollout and day-to-day operations Requirements At least 8 years of applicable professional background A minimum of 3 years spent in Senior, Lead, Manager, or Owner-level positions Demonstrated history managing engagements involving teams of 5 or more full-time staff Direct experience developing AI agents, spanning design, rollout, and refinement Familiarity with Amazon Web Services in support of cloud-hosted AI solutions Background evaluating and testing GenAI agents to confirm quality, reliability, and consistent performance Advanced capability in Python for constructing and validating AI-based workflows Working familiarity with REST APIs to facilitate integration across systems and tools Hands-on background with Retrieval-Augmented Generation (RAG) to anchor AI outputs in relevant source material Professional proficiency in English (C1) Nice to have Background working with AWS Bedrock to construct and launch generative AI solutions Knowledge of Amazon Bedrock AgentCore for assisting with agent coordination and management Experience applying MuleSoft to support integration across different systems Relevant certification, which would be considered a valuable addition to your qualifications [GTS] Benefits (generic, except India) International projects with top brands Work with global teams of highly skilled, diverse peers Healthcare benefits Employee financial programs Paid time off and sick leave Upskilling, reskilling and certification courses Unlimited access to the LinkedIn Learning library and 22,000+ courses Global career opportunities Volunteer and community involvement opportunities EPAM Employee Groups Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn