Job Description
AI/ML Engineer
Location: Charlotte, North Carolina (Hybrid)
Duration: 12 months
Payrate: $60-65/hr
Role Overview
We are seeking a skilled AI Engineer to design, develop, and deploy advanced AI/ML systems. This role is centered on building next-generation agentic AI solutions powered by retrieval-augmented generation (RAG), leveraging modern orchestration frameworks. The ideal candidate will have deep expertise in Python-based AI development and hands-on experience designing agent systems capable of reasoning, planning, tool usage, and executing complex multi-step workflows. This position involves primarily internal collaboration with cross-functional teams such as AI/ML engineers, UI developers, DevOps, and security/compliance stakeholders.
Key Responsibilities
- Design and develop production-grade Python APIs and services.
- Deploy and operate containerized applications on OpenShift, configuring manifests, services, routes, and secrets.
- Partner with AI/ML engineers to productionize model capabilities into usable backend services.
- Integrate backend APIs with Angular-based front-end applications.
- Remediate security vulnerabilities in Python libraries, container images, and OpenShift deployment configurations.
- Design and implement advanced RAG pipelines using vector databases, embeddings, and knowledge graphs.
- Develop agentic AI systems using LangGraph for dynamic task planning, tool orchestration, and multi-agent workflows.
- Integrate Model Context Protocol (MCP) for standardized context sharing and agent communication.
- Design memory systems and contextual state management for agent continuity.
- Implement evaluation pipelines, prompt engineering strategies, and guardrails to ensure performance, safety, and reliability.
- Apply Model Risk Management (MRM) practices across the AI lifecycle, including model validation, explainability, and monitoring.
Required Qualifications
- Primary Skill: Artificial Intelligence/Machine Learning
- Secondary Skill: Python
- Tertiary Skill: Natural Language Processing
- Education: Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Experience:
- Proven experience deploying LLM-powered production systems.
- Hands-on experience with agentic AI frameworks, particularly LangGraph, and emerging standards such as Model Context Protocol (MCP).
- Strong experience designing and implementing advanced RAG architectures, including Graph RAG.
- Experience with LLM orchestration frameworks such as LangChain, LangGraph, and LlamaIndex.
- Hands-on experience with vector databases like FAISS, Pinecone, Weaviate, or Azure AI Search.
- Strong understanding of LLMOps/MLOps, including CI/CD, observability, monitoring, and performance optimization.
- Working knowledge of Model Risk Management (MRM) frameworks.
- Experience with model evaluation, benchmarking, and explainability tools.
- Technical Skills:
- Strong proficiency in Python programming, with experience building scalable AI/ML systems.
- Proficiency with Python ML/AI frameworks such as PyTorch, TensorFlow, and Scikit-learn.
- Deep understanding of agent orchestration patterns, including planning, reflection, tool usage, and multi-agent collaboration.
- Familiarity with AI safety and alignment techniques, including guardrails and bias mitigation.
- Proficiency with development tools such as GitHub, VS Code, and JIRA.
- Knowledge of RedHat OpenShift.
- Understanding of Natural Language Processing.
Preferred Qualifications
- Experience working in an Agile development methodology.
- Experience with Retrieval-Augmented Generation (RAG) and Large Language Models (LLM).
