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
