Staff Software Engineer (Artificial Intelligence)

About the Role We are looking for a Staff Software Engineer, AI with deep expertise to set the technical direction and define the architecture for advanced language and voice technologies that transform how patients and providers interact. In this strategic role, you will be a key contributor, mentoring senior engineers and driving Fabric’s most complex work across a range of AI and ML applications and techniques. This is a high-leverage, technical leadership position at the core of Fabric’s production engineering vision. You will work cross-functionally to pioneer novel and impactful applications of machine learning, agentic AI, and other modern technologies to meet Fabric’s existing and future business needs. What You'll Do As a Staff Software Engineer, AI, you will be instrumental in defining the technical roadmap and elevating the team’s capabilities in advanced AI concepts. Your primary responsibilities will include: Defining the end-to-end architecture for mission-critical ML/AI applications and owning the entire SDLC of those applications. Pioneering and driving the productionization of ML and AI features in Python, integrating them seamlessly with core backend services. Setting technical standards and providing mentorship to the engineering team, raising the overall technical bar and driving best practices. Partnering with product and medical teams to architect appropriate, responsible safeguards and business constraints for all AI outputs at a system level. Collaborating with engineering leadership to design and evolve robust interfaces for the Data Science team’s applications, so they can be used by a wide array of products across the organization. Leading the way in designing and implementing automated evaluation frameworks to rigorously measure the accuracy, fairness, and performance of our systems. Serving as the technical owner for existing NLP and AI diagnosis production components, overseeing their maintenance and strategic improvement. Developing and driving adoption of comprehensive analytics to monitor system performance, identify systemic bottlenecks, and strategically prioritize improvements. Leading the organization’s strategy for getting the most out of AWS Bedrock, focusing on resilience and cost-efficiency. Maintaining a technical vision by rapidly researching, prototyping, and introducing new AI tools, APIs, and architectures that align with company needs. Shaping Fabric’s long-term AI strategy and contributing significantly to the future of healthcare AI. Why You Might Be a Good Fit You care deeply about the mission: you are passionate about deploying technology that empowers patients to engage with healthcare quickly, easily, and effectively. You're an autonomous problem solver: you excel at breaking down complex problems in the AI space and finding effective solutions, operating with autonomy and ownership. You’re a leader in your field: you stay current on machine learning, foundation models, and algorithms related to text and text-to-speech technologies. You value robust and responsible AI: you are committed to building robust testing and monitoring systems that provide insight into real-time performance, and you are dedicated to developing safeguards for responsible AI use. You thrive on collaboration: you enjoy working cross-functionally across teams, integrating AI use cases into products by understanding their APIs and data systems. You're a clear communicator: you’re skilled at communicating complex ideas clearly to both technical and non-technical audiences. This Might Not Be The Right Fit If... You prefer a role that is focused purely on research rather than hands‑on, production-level engineering and deployment. You are not comfortable with the ambiguity and fast‑paced nature of developing cutting‑edge AI systems from the ground up. You prefer to work in a silo rather than collaborating closely with product, medical, and other engineering teams. You are not passionate about the specific application of AI to solve real-world problems in the healthcare industry. Your Qualifications You have a combination of the following experience and credentials appropriate to a Staff-level engineering leader: A masters’ degree in a related field, or; 8+ years of experience in software engineering or applied machine learning, with a strong focus on building real-world AI/ML systems, or; Strong experience in developing healthcare-specific AI/ML solutions; or Demonstrable experience developing novel, highly impactful AI/ML solutions that handle sensitive data. Proficiency in backend software engineering using Python. Solid understanding of embeddings and embedding databases. Familiarity with modern AI/ML frameworks and tools, with constant attention to new tools, trends, and technologies. Experience building and deploying cloud‑native applications on AWS. Demonstrated ability to bring models from research to production, solving for latency, scale, and reliability. Effective communication skills and the ability to work across disciplines in a fast‑paced, agile environment. Strong technical leadership skills, with a particular focus on growing and supporting a skilled, senior-level team. Bonus Points Prior work on multimodal AI interfaces or agent-based dialogue systems. Experience hosting, scaling, and fine‑tuning open-source models. A passionate interest in improving healthcare access and outcomes through applied AI. The national pay range for this role is $165,000.00 - $210,000.00 per year. Actual compensation will be determined by factors such as the candidate’s geographic market, experience, skills, and qualifications. Certain roles may also be eligible for additional compensation, including a comprehensive benefits package such as medical, dental, vision, unlimited PTO, and a 401(k) plan, stock options and bonuses. If your compensation requirement is greater than our posted range, please still consider applying; a determination can be made based on unique qualifications. Expected compensation ranges for this role may change over time. #J-18808-Ljbffr Fabric