Senior Manager (AI Engineering)

What we want to accomplish and why we need you Suki is creating a new category in the health-tech space: Ambient Clinical Intelligence. Our AI-native products and platforms help power clinical workflows via ambient presence. What does that mean? Currently, doctors use electronic health record systems to take notes on patient encounters. This is a digital version of the paper charts that you may have seen in your doctor’s office or on TV. These systems can be hard to navigate and time-consuming to manage. Doctors would rather spend that time with patients. We are creating the solution using speech recognition, generative AI, and systems integration. Doctors that use Suki already spend over 70% less time on administrative tasks, and we’re striving to do even better. Come and join us! We are a user-driven company and are committed to making sure every pixel of our product is in service of the doctor. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine. We’re confident enough to move fast and talented enough not to break things. Check out this short video to learn more about our mission and our culture. Our tech stack includes GCP, Kubernetes, Golang, Python, React, TypeScript, JavaScript, Swift, Kotlin, gRPC, and GraphQL. What you will do every day As a Senior Engineering Manager for our AI Engineering team, you will serve as the strategic leader and mentor for our team of SF Bay Area based Machine Learning and Backend Engineers developing new Clinical Intelligence features alongside customers and partners. You will act as the bridge between ambitious product vision and technical execution, partnering closely with Product, Design, and Executive leadership to prioritize and execute on a roadmap that redefines the category. This role is responsible for project delivery from the ML data pipeline, to model and agent development, and the services/interfaces that will power our mobile and web clients, and public facing APIs. These services primarily perform inference, summarization, classification and transformation tasks. Previous experience using semantic, agentic, and structured RAG is expected. Candidates also need to have a strong background in software engineering and operations, and experience deploying high-concurrency, model-backed microservices atop Kubernetes. Given the rate of industry growth and change, the role requires staying up to date with technological advancements in AI, and suggesting & evaluating system design and inference approaches proposed by the team. You will build and iterate on features and services that directly impact thousands of clinicians, and improve their lives everyday Ok, you're sold, but what are we looking for in the perfect candidate? Expertise: Hands-on architectural and procedural experience working with ML-based systems and applications. Prior tech lead experience mandatory. Action oriented: Understands how perfect can be the enemy of good, and adjusts system design and staffing to best fit the functional and business objective. Creativity: Applies new algorithmic, agentic and fine-tuned model techniques as necessary, thinks through system design alternatives with the team to balance between good, fast, cheap. Humility: Collaborates with engineering leaders and senior ICs to build a collaborative culture across geographies where roles and responsibilities are understood and respected. Problem solving: Works on multiple tasks and prioritizes responsibilities within an Agile/Scrum environment. Partners well with Product and GTM teams. Ownership: Understands production systems, deployments and ensures application performance and uptime. Craftsmanship: Maintains high standards of code quality through evangelisation of unit testing, integration tests, and user experience. Requirements: 7+ years of total experience in Software Engineering management, with at least 3 years specifically leading high-performing teams of ML