Principal AI Engineer

Surescripts

3d•$187,500 - $229,100•Hybrid

About The Position

Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. We deliver insights at critical points of care for better decisions — from streamlining prior authorizations to delivering comprehensive medication histories to facilitating messages between providers. The Principal AI Engineer is the most senior individual contributor and technical lead for Surescripts’ AI solutions. The role owns the how, the execution, and the by-when for AI initiatives across the enterprise, pairing deep hands-on engineering with the architecture and business judgment to act as a trusted technical partner to product management, engineering, design, and business stakeholders. The Principal AI Engineer is accountable for technical feasibility, business alignment, and responsible AI practice across Surescripts’ platforms. This person designs and delivers AI solutions for both customer-facing products and the internal operations that support Surescripts team members, helping product teams deliver AI that is scalable, reliable, and something they can stand behind.

Requirements

Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent experience
8+ years of related, progressive software, data, or AI/ML engineering experience
4+ years in a lead and/or senior engineering role with a focus on leading and mentoring engineers to deliver software products
3+ years of hands-on machine learning / AI engineering experience
Proven experience architecting and delivering solutions across multiple technical domains, such as APIs and microservices, systems integration and event-driven architectures, AI/ML engineering, data engineering and analytics, and core software engineering (cloud-native applications, distributed systems)
Valid U.S. work authorization allowing work without restrictions with Surecripts in the U.S.

Nice To Haves

3+ years developing and implementing AI solutions in a healthcare setting
Experience designing production AI/ML applications using big-data technologies, cloud platforms (AWS, Azure, GCP), and data pipeline orchestration
Experience working in the SVPG framework or a substantially similar outcomes-driven product operating model

Responsibilities

Own the technical how and the delivery timeline for AI initiatives, acting as both AI solution architect and principal engineer.
Architect and build scalable, interoperable, responsible AI solutions, including generative AI, RAG, agentic AI, and predictive models, and guide their deployment into production.
Serve as a trusted technical partner across groups and projects, providing solution architecture and weighing options on technical feasibility, effort, and performance targets.
Translate business and customer needs into technical requirements, and frame technical options and trade-offs so leaders and stakeholders can make informed decisions that line up with business outcomes.
Lead the technical evaluation of new AI technologies and vendors, judging architectural fit, capability, and integration approach.
Prototype and validate advanced AI approaches to prove out architectural direction and de-risk initiatives before teams commit to them.
Run architecture and design reviews across teams, surfacing key trade-offs and keeping decisions transparent and sound.
Set and evolve AI engineering standards, including model integration, data architecture, LLMOps, AgentOps, and AI development best practices from frameworks such as NIST RMF, CHAI, OWASP, etc.
Serve as a lead mentor regarding enterprise AI Trust & Safety best practices from: auto-inherited controls and guardrails based on AI solution type and risk level, to automated evals and testing in CI/CD, to operational monitoring and drift detection, to issue and incident response, to data-driven continuous improvement of AI solutions.
Ensure the necessary technical components are designed-in and operationally effective to meet anti-bias, accuracy, transparency, explainability, safety, and regulatory compliance.
Mentor engineers and raise the technical bar, building a team culture of collaboration and steady learning.
Keep current with new AI technologies and frameworks and turn trends into practical strategies for the teams you support.