Machine Learning Engineer

Machine Learning Engineer

Richmond Virginia (5 Days Onsite) need local within commute

About the Role
We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design build and deploy next-generation AI this role you will work at the intersection of LLMs autonomous agents retrieval-augmented generation (RAG) and enterprise-scale systems leveraging Azure AI Foundry Copilot Studio and modern orchestration frameworks.
You will collaborate closely with product managers architects and application teams to deliver intelligent production-grade AI agents that integrate seamlessly with business workflows and enterprise data.

Key Responsibilities
Design and implement agentic AI systems capable of planning tool use memory and multi-step reasoning
Build and deploy AI solutions using Azure AI Foundry and Copilot Studio
Develop RAG pipelines integrating structured and unstructured enterprise data
Implement and optimize vector databases for semantic search and long-term agent memory
Orchestrate LLM-based agents using frameworks such as LangChain (or equivalent)
Develop scalable backend services and APIs using Python
Integrate AI agents with enterprise tools APIs and workflows
Evaluate monitor and optimize agent performance reliability and cost
Apply responsible AI principles including security privacy and governance
Stay current with advancements in LLMs agent architectures and Azure AI services

Required Qualifications
Bachelors or Masters degree in Computer Science Engineering or a related field
5 years of experience in machine learning AI engineering or applied ML
Strong proficiency in Python for ML and backend development
Hands-on experience building LLM-based applications
Practical experience with agentic AI patterns (tool calling planning memory reflection)
Experience with LangChain or similar agent orchestration frameworks
Solid understanding of RAG architectures
Experience with vector databases (e.g. Azure AI Search Pinecone etc.)
Familiarity with Azure cloud services and enterprise-grade deployments
Hands-on experience with MCP and/or A2A agent communication frameworks

Preferred Qualifications
Direct experience with Azure AI Foundry and Copilot Studio
Experience integrating AI agents into enterprise workflows or SaaS platforms
Knowledge of prompt engineering evaluation frameworks and guardrails
Experience with CI/CD MLOps or AI observability
Understanding of security identity and compliance in enterprise AI systems

Nice-to-Have
Contributions to AI prototypes internal platforms or open-source projects
Experience moving AI solutions from prototype to production
Strong communication skills and ability to explain complex AI systems to non-experts