Agentic AI Engineer

Agentic AI Engineer

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 someone who:

• Partners effectively with executives and business leaders to solve operational challenges.
• Understands complex operational data, large semantic models, Power BI 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 include:

• 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.
• Enterprise Integration
• Connect AI agents with CRM platforms such as Salesforce and Hub Spot.
• Healthcare and dental EMR systems.
• Databases, internal APIs, and SaaS applications.
• Power BI semantic models, datasets, reports, and embedded analytics environments.
• Retrieval-Augmented Generation (RAG) solutions leveraging company knowledge repositories.
• Authentication, authorization, and secure function-calling mechanisms.
• Platform Engineering
• 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 Power BI-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 include:

• 3–5+ years of software engineering experience.
• Strong Python development background.
• Experience building applications utilizing LLM APIs such as OpenAI, Anthropic, or Google.

Experience with:

• Healthcare or dental EMR platforms.
• Lang Graph
• Lang Chain
• CrewAI
• Auto Gen / Microsoft Agent Framework
• MCP-enabled systems
• API integrations
• SQL and relational databases
• Power BI, including semantic models, DAX, datasets, and report integrations.
• AWS, Azure, or GCP cloud environments.

Preferred qualifications include:

• Vector databases including Pinecone, Weaviate, or pgvector.
• Retrieval-Augmented Generation (RAG) architectures.
• Agent evaluation frameworks.
• CI/CD and Dev Ops practices.
• Docker and Kubernetes.
• Knowledge graph implementation.
• Prompt engineering and model tuning.
• Experience leveraging Power BI as an input, output, or orchestration layer within AI-driven workflows and enterprise automation initiatives.

Success metrics include:

• 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.

Compensation & benefits include:

• $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.