Note: The job is a remote job and is open to candidates in USA. EPAM Systems is seeking a Chief Generative AI Engineer to design, build, and operationalize a multi-agent AI contact center solution for a customer-facing conversational AI workstream. The role focuses on LLM orchestration, prompt engineering, guardrails, automated evaluation and hallucination detection, CI/CD quality gates, and production optimization using AWS cloud-native services and Amazon Connect.
Responsibilities
- Architect multi-agent workflows on Amazon Bedrock AgentCore, defining agent roles, tool contracts, memory strategy, and hand-off patterns across the conversation lifecycle
- Design prompt architectures, system instructions, and context-assembly patterns that hold up under production traffic and adversarial input
- Define guardrail and compliance controls, including PII redaction, topic denial, grounding constraints, and safe-fallback paths, aligned to customer regulatory obligations
- Build and iterate agent orchestration logic, tool/function integrations, and retrieval flows using Python on serverless AWS services
- Implement structured prompt versioning and experimentation so that changes remain traceable and reversible
- Integrate agentic capabilities with contact center telephony and chat channels, including deflection, escalation, and live-agent hand-off flows
- Build automated test and evaluation pipelines using LLM-as-a-Judge, golden datasets, and rubric-based scoring for accuracy, tone, grounding, and task completion
- Implement hallucination detection and grounding validation with quantified thresholds and regression tracking across model and prompt versions
- Wire evaluation gates into CI/CD so that no prompt, model, or agent change ships without passing quality and safety criteria
- Instrument observability, including traces, token accounting, latency, containment, and deflection rate, and drive tuning for cost and performance in production
- Act as deputy to the Technical Lead, covering technical decision-making, customer-facing reviews, and delivery continuity during Lead absence, and mentor engineers on agentic and evaluation practices
Skills
- - A minimum of 7 years of relevant experience
- - At least 2 years of leadership and team management experience
- - Experience in generative AI engineering, including LLM application design, prompt engineering, RAG, and model selection/tuning tradeoffs
- - Experience designing agentic and multi-agent workflows, including orchestration, tool use, memory, and hand-off patterns
- - Experience with LLM-as-a-Judge and automated evaluation, including rubric design, golden datasets, hallucination detection, and regression harnesses
- - Experience with Amazon Bedrock and Bedrock AgentCore
- - Strong Python skills for production AI services
- - Experience with AWS serverless architecture, including Lambda, Step Functions, API Gateway, DynamoDB, EventBridge, and CI/CD automation
- - Excellent English proficiency (B2 level or higher)
- - Experience with Amazon Connect, including contact flows, Lex integration, and Contact Lens
- - Familiarity with Responsible AI, guardrails, and compliance frameworks for regulated industries
- - Experience with observability and cost/latency optimization for LLM workloads
- - Experience with Infrastructure as Code tools such as CDK or Terraform
Benefits
- 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
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