Role Description 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 - Define the end-to-end architecture for mission-critical ML/AI applications and own the entire SDLC of those applications. - Pioneer and drive the productionization of ML and AI features in Python, integrating them seamlessly with core backend services. - Set technical standards and provide mentorship to the engineering team, raising the overall technical bar and driving best practices. - Partner with product and medical teams to architect appropriate, responsible safeguards and business constraints for all AI outputs at a system level. - Collaborate 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. - Lead the way in designing and implementing automated evaluation frameworks to rigorously measure the accuracy, fairness, and performance of our systems. - Serve as the technical owner for existing NLP and AI diagnosis production components, overseeing their maintenance and strategic improvement. - Develop and drive adoption of comprehensive analytics to monitor system performance, identify systemic bottlenecks, and strategically prioritize improvements. - Lead the organization's strategy for getting the most out of AWS Bedrock, focusing on resilience and cost-efficiency. - Maintain a technical vision by rapidly researching, prototyping, and introducing new AI tools, APIs, and architectures that align with company needs. - Shape Fabric’s long-term AI strategy and contribute significantly to the future of healthcare AI. Qualifications - A master's 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. Requirements 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.

• Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments. • Develop end-to-end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments. • Integrate and optimize LLMs for specific business planning use cases, including prompt engineering and RAG implementation. • Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language • Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics • Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations • Optimize model inference pipelines for performance, cost, and scalability in production environments • Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behavior. • Collaborate with data scientists to productionise ML models and forecasting algorithms

• Own the design, development, testing, and support of full-stack features across .NET backend services and Angular frontend applications • Build and maintain APIs and microservices in a distributed, cloud-native architecture • Contribute to container orchestration and deployment workflows using Azure Kubernetes Service (AKS) and Docker • Collaborate with product managers, architects, and cross-functional Agile teams to translate business requirements into robust technical solutions • Participate in code reviews, architectural discussions, and sprint ceremonies; provide technical mentorship to junior engineers • Identify and address performance, reliability, and scalability gaps across assigned services • Leverage AI-assisted development tools (such as Claude Code) to accelerate implementation, code review, and documentation workflows • Support production systems, contribute to incident retrospectives, and implement preventive engineering improvements • Stay current with emerging technologies and advocate for engineering best practices within the team

• Design, develop, and maintain APIs, services, and interfaces that support the entire acquisition flow (landing pages, signup, login, trials, and onboarding). • Build server-side and front-end logic to support A/B tests, feature flags, and conversion optimization experiments. • Integrate our platform with essential growth tools such as CRMs (HubSpot, Salesforce), payment gateways (Stripe), marketing automation, and analytics tools (Segment, Mixpanel). • Ensure optimal loading performance (Core Web Vitals) and apply technical SEO best practices to boost organic acquisition. • Write clean, semantic code covered by automated tests, ensuring a secure and resilient architecture for traffic spikes. • Collaborate with the data team to segment users and instrument the front end to capture interaction metrics (GA4, Mixpanel). • Support developer growth and promote a culture of continuous learning. • Collaborate with cross-functional teams to define and evolve architecture, processes, and technical solutions. • Act as a bridge between developers and Engineering Managers, ensuring technical alignment, efficient prioritization, and excellence in delivery.