Principal, AI Solutions & Implementation

Responsibilities
Strategic AI Vision & Execution: Contribute to the broader enterprise AI strategy by identifying high-value opportunities and ensuring that practical, hands-on pilot projects align with Quest’s long-term operational goals

End-to-End Project Execution: Personally lead the hands-on delivery of AI projects, from initial concept and prototyping through to full-scale implementation, monitoring, and optimization

Hands-On Development & Implementation: Act as the primary technical and operational driver for AI initiatives. You will partner with functional teams to build proof-of-concept models and manage the project lifecycle to ensure successful delivery

Proven Pilot Delivery: Leverage your hands-on experience to rapidly develop and validate AI pilots that demonstrate clear ROI and operational benefits before scaling

On-Site Deployment & Validation: Travel to physical facilities (labs, operational centers) during critical AI deployments to provide on-the-ground support. Drive go-live execution, troubleshoot real-time issues, and conduct rigorous post-go-live validation to guarantee the solution delivers the expected ROI and workflow improvements

Cross-Functional Partnership: Act as the key liaison between operational teams, IT, and external vendors, ensuring seamless collaboration to deliver robust and scalable solutions

Capability Building: While this role has no direct reports, you will coach and mentor a network of “AI Champions” embedded within functional teams, helping to build decentralized AI skills and foster a culture of practical innovation

Governance & Regulatory Compliance: Partner closely with the AI Review Board and Quest Governance teams to evaluate and safely navigate risk. Ensure all models, workflows, and AI initiatives maintain strict compliance with HIPAA, PHI regulations, and internal data security protocols

Change Management & Adoption: Go beyond the technical deployment to drive actual user adoption. Develop repeatable playbooks for rollout, monitor usage metrics, and guide operational and clinical staff through the transition to AI-enabled workflows with empathy and clear communication

Vendor & Ecosystem Management: Rapidly evaluate, pre-screen, and integrate third-party AI tools (e.g., LLMs, Copilot agents, iPaaS platforms). Act as the technical SME to ensure vendor solutions align with Quest’s enterprise architecture and strict security standards

Qualifications
Education: Bachelor’s degree in Business, Computer Science, Engineering, Information Systems, Data Science, or related field (Required). Master’s degree in Business Administration (MBA), Artificial Intelligence, Data Science, Analytics, or related field (Preferred).

AI Expertise: Demonstrated hands-on expertise in deploying and integrating various AI modalities, including Optical Character Recognition (OCR), Computer Vision, Large Language Models (LLMs), and Agentic AI systems.

Enterprise Delivery: Proven, hands-on experience delivering enterprise AI or generative AI solutions through successful pilots and scaled deployments (Required).

Technical Proficiency: Hands-on technical proficiency with AI tools and integrations, which may include prompt engineering, API/Webhook integrations, or experience with major cloud AI services (e.g., Azure AI, AWS).

Healthcare Integration: Experience integrating technology into complex healthcare systems (e.g., Electronic Health Records (EHR), Laboratory Information Systems (LIS), or operational platforms) is highly preferred.

Execution Style: Ability to act as a self-directed “team of one,” driving complex projects from ideation to completion (Required).

Experience: 10+ years of experience leading and execution AI initiatives, 5-7 of those years must be in a hands-on role related to data science, AI implementation, or technology delivery in a large enterprise environment.

Automation & Operations: Strong familiarity with workflow automation, low-code/no-code platforms, or robotic process automation (RPA) (Required). Deep understanding of operational functions (e.g., logistics, supply chain, customer service, lab operations).

Business Acumen: Strong business acumen with experience building business cases and measuring ROI for technology initiatives.