AI/ML Engineer

Company Description VRPRO IT LLC provides organizations with comprehensive workforce services, including temporary career opportunities, independent contracts, corp-to-corp agreements, contract-to-hire, and direct placements. Using innovative strategies and a strong ethical foundation, VRPRO IT delivers exceptional solutions to its clients. Known for its commitment to quality and professionalism, the company has earned the trust and appreciation of its clients as a valuable business partner. This role is an AI/ML Engineer focused on GenAI, RAG, and Agentic AI, built Azure-first. Azure isn’t just the hosting environment; it’s the backbone of how the solution is designed and implemented. The engineer will build custom RAG pipelines using Azure services like Blob Storage, Data Factory, and Azure Document Intelligence, with Python code handling chunking, embeddings, retrieval logic, and agent workflows. This is a hands-on, client-facing role. The engineer runs meetings, demos solutions directly to the client, and operates in a fast-paced environment. This is not a prompt-engineering or research role. Only W2 Role/USC/GC Must-Have Skills • Experience with GenAI systems/Agentic AI, including RAG, embeddings, and LLM integration • Familiarity with agentic or multi-agent AI workflows • Experience building scalable, production-ready AI platforms • Strong Python expertise with experience building production APIs (FastAPI, Flask, or equivalent) - (production-level) meaning the person can build, ship, and support real systems in production, not just write scripts or notebooks • FastAPI preferred; Flask/Django acceptable) - FastAPI needed but anyone can learn it if they know Python well and if they have done any REST APIs (using flask, Django, etc. • Proven experience designing and deploying AI systems end-to-end, not just POCs • Building AI solutions in Azure. • Azure OpenAI / Cognitive Services - Azure OpenAI and Cognitive Services provide the AI capabilities, while Blob Storage, Data Factory, and Cloud Foundry are the Azure platform services used to store data, orchestrate pipelines, and run the production system. • They have to understand how to process PDFs • Experience with vector databases and retrieval strategies • Exposure to data pipelines and orchestration (e.g., Azure Data Factory, Databricks) Excellent verbal communication - SOMEONE WHO IS SHARP AND ARTICULATE • Comfortable on video and running meetings • Can explain AI outputs in business terms • Ability to clearly explain technical AI concepts to engineers and stakeholders • Able to operate independently in a fast-paced environment • They have to be super technical, hands-on, address problems quickly, and able to work in a very fast-paced environment. • Getting ahold of finance teams is hard so they have to be ok with that • Bachelor’s degree is ideal but if they do not have one still will be considered