AI Solutions Engineer

Health Data Innovations • Cleveland, OH

1d • Hybrid

About The Position

Health Data Innovations (HDI) is seeking an AI Solutions Engineer to build and operate AI tools, integrations, workflows, and agents across the company, leading its transition to agentic AI. HDI’s AI initiative already includes enterprise AI assistants and coding tools, a private model gateway on Amazon Bedrock, custom business-system connectors, and local models running on GPU hardware. The role will help advance those capabilities by building agents that take action across systems.

This is a hands-on position on a small team. Most time will be spent building AI solutions and agents, with the remainder supporting their infrastructure, including cloud services, identity, servers, and GPU hosts. The work takes place in a security-first, HITRUST-governed environment and involves close collaboration with executives and business functions to identify opportunities for AI across the company.

The role is hybrid, with periodic in-office presence in Cleveland required for team meetings, onboarding and training, and scheduled stakeholder collaboration during planning and rollout phases.

Requirements

• At least 3 years of experience in IT infrastructure, systems administration, DevOps, or software development.
• Hands-on experience building with LLMs or AI agents, including tool use, MCP, or multi-step workflows; experience may come from work, prototypes, or personal projects.
• Experience with LLM APIs or cloud AI platforms such as Amazon Bedrock, Azure OpenAI, or Vertex AI.
• Solid Linux skills (RHEL or Ubuntu), plus working knowledge of Windows Server and Docker.
• Networking and security fundamentals, including firewalls, segmentation, and least privilege.
• Scripting and automation skills; Python is preferred, with PowerShell or Bash a plus.
• Experience integrating with APIs, databases, and business systems.
• Familiarity with Git workflows and code review.
• Curiosity about AI and the discipline to turn experiments into reliable, documented systems.
• Ability to work independently, manage priorities, and support non-technical users in a small-team environment.

Nice To Haves

• Experience building MCP servers or using agent frameworks.
• Experience taking an agent from prototype to production.
• Experience testing and evaluating LLM output.
• Software development experience in Python, Go, or TypeScript.
• Experience with RAG pipelines and vector databases such as pgvector, Qdrant, Chroma, or Milvus.
• Experience with Entra ID / Azure AD, SSO, and OAuth 2.0 / OIDC.
• Experience working under a compliance framework such as HITRUST, HIPAA, SOC 2, or ISO 27001.
• AWS IAM, cost management, and Bedrock guardrails experience.
• Local AI experience running open-weight models with vLLM or llama.cpp on NVIDIA GPUs, including vGPU or GPU passthrough.
• Experience with Remote Desktop Services, Azure Arc, and virtualization such as VMware, Proxmox, or Hyper-V.
• Experience with OpenTelemetry, Prometheus, or Grafana.
• MySQL Server or PostgreSQL administration experience.
• Experience with Microsoft Graph API.
• Experience with Terraform, Ansible, or Packer.

Responsibilities

• Work with business users to identify processes where AI can help and determine whether an assistant, AI-assisted workflow, or agent is the right approach.
• Build and improve AI-assisted workflows, skills, and plugins for everyday processes.
• Lead the transition to agentic AI by designing, building, and deploying agents and multi-step workflows using tool use or function calling, prompt and context design, and agent frameworks.
• Build and support Model Context Protocol (MCP) servers, database bridges, and Microsoft 365 integrations so AI tools and agents can safely access necessary data and systems.
• Test and evaluate AI output for accuracy and reliability, and identify regressions before they reach users.
• Implement guardrails, least-privilege permissions, human-in-the-loop approvals, and audit logging, especially when AI interacts with sensitive healthcare data.
• Own AI solutions in production by monitoring behavior, usage, and cost; troubleshooting issues; and versioning, maintaining, and retiring solutions.
• Write scripts and code, mainly in Python, managed through Git and pull-request review.
• Track new models, agent frameworks, and vendor releases; run proofs of concept; and recommend what to adopt.
• Support infrastructure behind AI services, including Amazon Bedrock, Entra ID and SSO, Linux and Windows servers, virtual machines, and GPU hosts.
• Write documentation, runbooks, and guides suitable for compliance audits.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed