Artificial Intelligence Engineer

Location: Charlotte, NC with a hybrid schedule (3 Days Onsite/2 Days Remote) Salary: $140,000–$175,000 Base + 10–15% Bonus Position Summary A rapidly growing healthcare services organization is seeking its first Agentic AI Engineer to help shape and deploy enterprise‑wide AI capabilities. This newly created role offers a unique opportunity to work directly with executive leadership and business stakeholders to understand operational processes, identify automation opportunities, and deliver production‑ready agentic AI solutions. Unlike traditional architecture‑focused positions, this role is centered on implementation, experimentation, and execution. The ideal candidate is a builder who enjoys moving quickly from concept to deployment and thrives in environments where requirements are evolving and ambiguous. We are seeking an ideal candidate who: Partners effectively with executives and business leaders to solve operational challenges. Understands complex operational data, large semantic models, PowerBI semantic models and reporting environments, and modern AI tooling to investigate business questions. Can take an ambiguous business problem and build a working AI solution that generates actionable insights. Is comfortable working with tools such as Codex, Claude Code, Cursor, and modern agent frameworks. Understands enterprise systems, integrations, and business processes. Focuses on delivery and execution rather than high‑level solution architecture. Has experience developing agents that reconcile insurance data, summarize clinical or operational records, automate procurement variance analysis, and trigger workflows in enterprise systems. Understands the importance of protecting PHI and sensitive employee information. Key Responsibilities: AI Agent Development Design and develop AI agents utilizing LLMs and agent frameworks. Build multi‑agent workflows for enterprise use cases. Implement reasoning, planning, memory, and tool‑use capabilities. Develop reusable agent templates and autonomous workflows integrated with enterprise applications. Incorporate PHI/HIPAA‑aware development practices including RBAC, audit logging, least‑privilege access, prompt injection defense, evaluations, and human approval mechanisms for high‑risk actions. Connect AI agents with: CRM platforms such as Salesforce and HubSpot. Healthcare and dental EMR systems. Databases, internal APIs, and SaaS applications. PowerBI semantic models, datasets, reports, and embedded analytics environments. Retrieval‑Augmented Generation (RAG) solutions leveraging company knowledge repositories. Authentication, authorization, and secure function‑calling mechanisms. Develop and maintain agent orchestration workflows. Monitor agent reliability, performance, and operating costs. Build testing, evaluation, observability, and logging frameworks. Optimize prompts, workflows, and tool utilization. Delivery & Collaboration Partner with business teams to identify automation opportunities. Translate operational requirements into agentic AI solutions. Partner with Finance and business leaders to augment existing reporting processes, including PowerBI‑based analyses and operational insights, with agentic AI solutions. Rapidly prototype and iterate on AI‑driven workflows. Document implementation standards and mentor junior developers on best practices. Required Qualifications 3–5+ years of software engineering experience. Experience building applications utilizing LLM APIs such as OpenAI, Anthropic, or Google. Experience with: LangGraph LangChain CrewAI AutoGen / Microsoft Agent Framework MCP‑enabled systems API integrations SQL and relational databases PowerBI, including semantic models, DAX, datasets, and report integrations. AWS, Azure, or GCP cloud environments. Preferred Qualifications Vector databases including Pinecone, Weaviate, or pgvector. Retrieval‑Augmented Generation (RAG) architectures. CI/CD and DevOps practices. Docker and Kubernetes. Knowledge graph implementation. Prompt engineering and model tuning. Experience leveraging PowerBI as an input, output, or orchestration layer within AI‑driven workflows and enterprise automation initiatives. Success Metrics Number of production AI agents delivered. Workflow automation hours saved. Agent reliability and task completion rates. Reduction in manual processes. User adoption and satisfaction. Cost efficiency of deployed solutions. Time‑to‑deployment for new agent solutions. $140,000–$175,000 base salary plus 10–15% annual bonus. Hybrid work arrangement with three days per week onsite in Charlotte, NC. Comprehensive benefits package including medical, dental, vision, life insurance, wellness programs, 401(k), paid holidays, competitive PTO, paid parental leave, and annual incentive opportunities. #J-18808-Ljbffr Addison Group