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Job Description

The Agentic AI Engineer will design, build, deploy, and maintain AI-powered agents and multi-agent systems that automate business processes and integrate with enterprise applications. The role is hands on and includes HIPAA-aware, secure development, along with agent development, platform engineering and observability, and collaboration through documentation.

Responsibilities

  • Design and build AI agents using LLMs and agent frameworks including LangChain, LangGraph, CrewAI, and AutoGen.
  • Develop multi-agent workflows for enterprise use cases such as insurance reconciliation, clinical record summarization, and procurement automation.
  • Implement agent capabilities including reasoning, planning, memory, and tool use.
  • Connect agents to enterprise systems, including Salesforce, HubSpot, EMR systems, internal APIs, databases, and SaaS applications.
  • Build RAG solutions using company knowledge bases.
  • Apply HIPAA-aware development practices such as RBAC, audit logging, least-privilege tool access, and prompt-injection defense.
  • Monitor agent performance, reliability, and cost by building evaluation and observability frameworks.
  • Rapidly prototype and iterate on AI-driven workflows with direct input from business stakeholders.
  • Mentor junior developers on agentic AI development practices.

Time allocation: 70% AI Agent Development & Enterprise Integration, 20% Platform Engineering & Observability, 10% Collaboration & Documentation. 100% hands on.

Required Skills & Experience

  • Python
  • LLM APIs (OpenAI, Anthropic, Google, etc.)
  • LangChain / LangGraph
  • CrewAI / AutoGen / Microsoft Agent Framework
  • API Integration
  • SQL / Database knowledge
  • Cloud platforms (AWS, Azure, or GCP)
  • MCP-enabled systems
  • Healthcare / Dental EMR systems (e.g., DSN Cloud, WinOMS)

Desired Skills

  • 3-5+ years of software engineering experience
  • BS or MS in Computer Science or related field
  • Experience with vector databases (Pinecone, Weaviate, pgvector)
  • Retrieval-Augmented Generation (RAG) architectures
  • Containerization (Docker / Kubernetes)
  • CI/CD and DevOps practices
  • Prompt engineering and model tuning
  • Agent evaluation frameworks
  • Knowledge graph implementation
  • Familiarity with AI coding tools (Codex, Claude Code, Cursor)
  • Strong communicator and self-starter

Technologies

Python, LLM APIs, OpenAI, Anthropic, Google, LangChain, LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, SQL, AWS, Azure, GCP, MCP-enabled Systems, DSN Cloud, WinOMS, Salesforce, HubSpot, RAG, HIPAA, RBAC.

Benefits

  • Competitive Base Salary + Bonus + Equity / Long-Term Incentive
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)

Location

Charlotte, NC (onsite)

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