AI Solutions Engineer

The AI Solutions Engineer designs, implements, and continuously improves AI capabilities, both in MEDHOST products and in the tools our teams use to build them.

This person turns business and clinical problems into secure, compliant, production-ready AI solutions.

They also lead the design and improvement of our internal AI tools.

You’ll partner with Product, Engineering, QA, Security, and Compliance to turn AI ideas into working, production-quality solutions.

As a trusted advisor to business and technical stakeholders, you’ll spread proven practices across teams and work directly with customers to support AI solution design and rollout.

You’ll help define the patterns, guardrails, and evaluation standards that let teams build and run AI features safely and repeatably.

The AI Solutions Engineer is remote within the U.S.

and Canada.

Key Responsibilities:


* Deliver AI-powered product features and agents, deployed either in products for customers or as internal digital workers


* Build end-to-end agentic AI systems, including orchestration, tool use, memory, model routing, failure handling, and cost control.

Identify when a deterministic workflow is the better fit, and keep the platform current as new models and frameworks emerge


* Lead AI-accelerated delivery from prototype to production.

Integrate models and agents with enterprise knowledge, APIs, tools, and transactional systems


* Work directly with customers as needed to understand requirements, support AI deployments, and gather feedback


* Establish practices for AI evaluation, regression testing, observability, drift, latency and cost monitoring


* Capture and codify lessons learned from implementation work into shared best practices, including a consistent AI-DLC methodology for applying AI across the product development lifecycle


* Run hands-on early-stage initiatives, proof-of-concepts, and first-of-a-kind projects to validate feasibility, unblock teams, or accelerate product development


* Define, track, and report KPIs for AI solutions in both product and internal tools (for example, output quality, accuracy, reliability, cycle time, rework, and cost).

Share results with stakeholders regularly and use them to prioritize improvements


* Champion responsible AI principles, including fairness, transparency, privacy, and accountability


* Facilitate workshops and deliver presentations focused on AI best practices

 

 

Requirements and Qualifications:


* Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience) and 5+ years of software engineering or architecture experience


* Proven experience leading or influencing initiatives across product, business, and technical domains


* Strong understanding of core AI concepts, including large language models, ML workflows, prompt and context engineering, and agent orchestration


* Hands-on technical depth.

Strong, demonstrated experti...