
51 - 200 employees
🏥 Healthcare
đź’Ľ Consulting
📦 Logistics
Healthcare • Consulting • Logistics
<Trio Workforce Solutions> Trio Workforce Solutions is a healthcare-focused workforce management company that provides Vendor Management System (VMS), Managed Service Provider (MSP), and related SaaS solutions to health systems, physician practices, diagnostic imaging centers, and staffing agencies. It combines cloud-based technology, market intelligence, analytics, AI-enabled candidate evaluation and credentialing, and operational support to optimize contingent staffing, reduce costs, accelerate hiring, and manage internal and external talent pools. Trio emphasizes measurable outcomes and enterprise-level advisory services, positioning itself as a B2B partner that helps healthcare organizations centralize and take control of their workforce strategy.
đź•’ September 21
🌪️ Oklahoma, Texas – Remote
đź’µ $150k - $180k / year
⏰ Full Time
đźź Senior
🤖 AI Engineer
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51 - 200 employees
🏥 Healthcare
đź’Ľ Consulting
📦 Logistics
Healthcare • Consulting • Logistics
<Trio Workforce Solutions> Trio Workforce Solutions is a healthcare-focused workforce management company that provides Vendor Management System (VMS), Managed Service Provider (MSP), and related SaaS solutions to health systems, physician practices, diagnostic imaging centers, and staffing agencies. It combines cloud-based technology, market intelligence, analytics, AI-enabled candidate evaluation and credentialing, and operational support to optimize contingent staffing, reduce costs, accelerate hiring, and manage internal and external talent pools. Trio emphasizes measurable outcomes and enterprise-level advisory services, positioning itself as a B2B partner that helps healthcare organizations centralize and take control of their workforce strategy.
• Own the architecture of the Digital Worker platform and AI capabilities embedded in Trio's products • Establish design principles, engineering patterns, and architectural standards for AI systems • Lead technical design reviews and make tradeoff decisions on quality, latency, cost, and operational complexity • Evaluate emerging AI technologies and determine adoption priorities • Design and build production systems using LLMs, retrieval architectures, agentic workflows, and tool use • Build reusable frameworks for agent orchestration, tool integration, workflow execution, and memory • Solve the team's hardest technical problems hands-on • Own standards for measuring AI quality, including accuracy, groundedness, safety, latency, and business impact • Build and extend evaluation frameworks to detect regressions and hallucinations • Drive measurable system-quality improvements through experimentation and production learning • Define monitoring, tracing, and logging standards for production AI systems • Establish reliability and performance objectives and serve as senior escalation for critical AI production issues • Improve production readiness and AI lifecycle management as the platform scales • Mentor the AI Engineering team and develop architectural judgment and engineering depth • Lead code and design reviews and enforce engineering standards • Partner with Product, Platform, Data, Security, and executive stakeholders • Translate business objectives into technical strategy and technical tradeoffs into business terms • Extend the Digital Worker framework, evaluation infrastructure, platform orchestration, centralized inference, and retrieval and knowledge systems • Expected to assume formal leadership of the AI Engineering team as it grows
• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field, or equivalent practical experience • 7+ years in software engineering, data engineering, or a closely related technical field • 2+ years building and operating production LLM-powered systems • Demonstrated depth in agentic systems, RAG architectures, or AI orchestration frameworks • Solid understanding of machine learning fundamentals • Strong distributed systems and software architecture fundamentals • Professional proficiency in Python; comfort in a polyglot environment • Track record of evaluating AI system quality quantitatively and acting on the results • Experience mentoring engineers on technical and architectural decisions • Excellent written and verbal communication with technical and executive audiences • Preferred: Master's degree in Computer Science, AI, Machine Learning, or a related technical discipline • Preferred experience with team leadership or management, Azure cloud, Azure OpenAI, event-driven infrastructure, vector databases, semantic search, embeddings, enterprise knowledge systems, agent orchestration platforms, AI governance/security/compliance/responsible AI, .NET/C#, React/TypeScript, SQL Server, CosmosDB, Auth0, Azure DevOps, Datadog, and SaaS, workforce technology, healthcare, or high-growth technology organizations • Ability to perform essential functions with or without reasonable accommodation • Ability to remain stationary for approximately 50% of the workday, learn and apply new tasks and procedures, maintain attention, work independently, make timely workflow-related decisions, and meet productivity and/or time-based performance expectations
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