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We are looking for a Lead AI/ML Consultant (Agentic AI Engineer) for the ADP account engagement. This is a pivotal technical position centered on architecting and building agentic AI solutions powered by AWS services. The resource will head up the AI/ML workstream, partnering with Technical Business Analysts to bring GenAI capabilities to life for the client.

Responsibilities

Architect and build multi-agent AI systems, encompassing orchestration patterns, agent-to-agent delegation, tool/function calling, and memory management
Develop agentic AI solutions leveraging Amazon Bedrock Agents, Knowledge Bases, Guardrails, and Flows
Deploy solutions using agentic frameworks including LangGraph, LangChain, CrewAI, AutoGen, or comparable tools
Architect and build Retrieval-Augmented Generation (RAG) systems utilizing vector stores such as OpenSearch, Kendra, and Pinecone
Create and refine prompts for diverse LLM use cases, including evaluation workflows and hallucination reduction techniques
Integrate with various LLM providers, such as Claude, Amazon Nova, and Llama, through the Amazon Bedrock platform
Connect AI solutions with serverless components such as Lambda, Step Functions, API Gateway, S3, and DynamoDB
Establish guardrails, PII handling protocols, and enterprise compliance measures to ensure secure and responsible AI operations
Architect token-efficient designs and apply cost governance strategies to manage and optimize AI solution spending

Requirements

A minimum of 5 years of relevant experience
At least one year of experience leading and managing teams
Background in building agentic and multi-agent workflows that support orchestration, delegation, and autonomous task execution among AI agents
Direct experience with Amazon Bedrock for developing and deploying generative AI solutions, including agents, knowledge bases, and guardrails
Applied experience with LangChain/LangGraph for constructing and coordinating LLM-powered applications and agentic workflows
Experience architecting RAG (Retrieval-Augmented Generation) systems to anchor LLM outputs in accurate, relevant data
Advanced Python skills for building AI/ML applications, integrating models, and developing automation scripts
Experience in prompt engineering, covering the design, testing, and refinement of prompts to enhance LLM performance and reliability
Excellent English communication skills (B2 level or higher)

Nice to have

Experience with Amazon SageMaker for developing, training, and deploying machine learning models
Exposure to LLMOps practices for overseeing the full lifecycle of LLM-based applications, from deployment through monitoring and ongoing improvement
Understanding of vector databases for storing and retrieving embeddings to enable RAG and semantic search functionality

We offer

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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