What are the responsibilities and job description for the Senior AI/ML Engineer – Agentic AI (AWS) position at ServIT Consulting LLC?
ONLY W2 *ONLY W2 ONLY W2
USC/ EAD
NO SPONSORSHIP
Senior AI/ML Engineer – Agentic AI (AWS)
Location: Hybrid(3days in Charlotte NC)
Employment Type: Contract (W2 Only)
Job Summary
We are seeking a highly skilled Senior AI/ML Engineer with expertise in Agentic AI, Generative AI, Large Language Models (LLMs), and AWS Cloud to join our team on an onsite W2 contract. The ideal candidate will have 10 years of overall IT experience, including 4–5 years of hands-on experience in AI/ML and Generative AI, with proven expertise designing, developing, and deploying enterprise-grade AI solutions on AWS.
Key Responsibilities
· Design, develop, and deploy enterprise-scale Agentic AI and Generative AI solutions.
· Build autonomous AI agents capable of reasoning, planning, memory management, and tool invocation.
· Develop AI applications using LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
· Design and implement Retrieval-Augmented Generation (RAG) solutions using vector databases.
· Deploy and manage AI applications using Amazon Bedrock, SageMaker, Lambda, ECS/EKS, and other AWS services.
· Integrate AI models with enterprise applications, APIs, databases, and third-party platforms.
· Develop prompt engineering strategies and AI guardrails.
· Optimize AI models for scalability, performance, security, and cost efficiency.
· Collaborate with cross-functional teams to deliver production-ready AI solutions.
· Mentor junior engineers and contribute to AI architecture best practices.
Required Qualifications
· Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
· 10 years of IT/software engineering experience.
· 4–5 years of hands-on AI/ML, Generative AI, and LLM application development.
· Strong Python programming skills.
· Hands-on experience with Agentic AI, LLMs, RAG, Prompt Engineering, Vector Databases, MCP, Function Calling, and AI evaluation.
Preferred Qualifications
· Enterprise AI governance and Responsible AI.
· Multi-agent AI systems.
· MLOps and CI/CD for AI/ML pipelines.
· Integration with Salesforce, ServiceNow, SAP, or Microsoft 365.
· Banking, Financial Services, Insurance, or Healthcare experience.
· AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect certifications.
Additional Requirement
· Hybrid contract position.
· W2 Only. No C2C, 1099, or third-party candidates.