Note: The job is a remote job and is open to candidates in USA. Lifepoint Health is a leader in community-based care and is seeking a Senior Agentic AI Engineer to design, develop, and deploy AI-powered autonomous workflows. The role involves building LLM-powered workflows, integrating AI with enterprise tools, and ensuring the reliability and security of AI systems.
Responsibilities
- Design and build LLM-powered agentic workflows using Azure AI Foundry and Anthropic Claude APIs that automate business processes currently requiring manual human effort
- Develop multi-step AI agent pipelines using orchestration frameworks (e.g., LangChain, AutoGen, Semantic Kernel, or custom implementations) integrated with enterprise systems such as ServiceNow, Okta, and ERP platforms
- Implement Model Context Protocol (MCP) integrations to enable AI agents to securely access and act on enterprise data sources, tools, and APIs — becoming an internal subject-matter expert on MCP patterns and best practices
- Apply security-by-design principles throughout all AI agent development: prompt injection defense, least-privilege tool access, secrets management, output validation, and safe handling of sensitive organizational data
- Build, test, and iterate on prompts, system instructions, and agent reasoning chains to ensure reliable, accurate, and safe agent behavior across diverse business scenarios
- Partner with the Backend Integration Engineer to connect agent workflows to existing enterprise API infrastructure and MCP server endpoints
- Collaborate with the AI Business Analyst to translate business use cases into technical agent requirements and working prototypes
- Participate in code reviews, maintain internal documentation, and contribute to the team’s shared engineering standards for agentic AI development
- Stay current with rapidly evolving AI tooling, model capabilities, and agentic design patterns — proactively experimenting and bringing new techniques to the team
- Assist in evaluating AI agent outputs for accuracy, safety, and alignment with intended business outcomes before production deployment
- Designing multi-step autonomous workflows
- Integrating AI with enterprise tools and APIs
- Prompt engineering, orchestration, tool calling, RAG, and agent safety
- Turning business use cases into working AI solutions
- Ensuring AI systems behave reliably, securely, and accurately
Skills
- Bachelor's degree in computer science, Information Systems, Software Engineering, or related field preferred
- 4+ years of experience in a foundational IT, software engineering, systems integration, or application development environment required
- At least 2+ years of hands-on experience working with AI, automation, orchestration, or integration platforms such as Azure AI Foundry, Anthropic Claude APIs, LangChain, AutoGen, Semantic Kernel, ServiceNow, Okta, ERP-connected workflows, or similar enterprise automation technologies
- Practical experience building, supporting, or enhancing technical solutions in production or pilot environments
- Strong core competencies in programming, API integration, troubleshooting, and systems thinking
- Working knowledge of Python and REST API consumption and integration
- Familiarity with Azure cloud services
- Understanding of LLM concepts: prompting, tool use / function calling, context management, retrieval-augmented generation (RAG), and multi-agent orchestration
- Exposure to or eagerness to deeply learn Model Context Protocol (MCP)
- AI security awareness: prompt injection attacks, data leakage risks, insecure tool execution, jailbreaking techniques, and general OWASP software security principles
- Experience with version control (Git) and basic software development lifecycle (SDLC) practices
- Intellectual curiosity and a demonstrated self-directed learning habit
- Strong problem-solving skills and ability to operate independently in a fast-moving, ambiguous environment
- Excellent written and verbal communication skills
- Equivalent practical experience or a strong portfolio of AI projects will be considered
- Experience with agentic AI projects, whether in professional settings or through substantial independent work, is strongly preferred
- Azure AI Foundry experience is a strong plus
- Microsoft Azure AI Engineer Associate (AI-102) or Azure Fundamentals (AZ-900) preferred
- Willingness to pursue relevant AI and Azure certifications is expected and supported by the organization
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