Senior Applied AI Engineer (San Francisco)

About AlembicAlembic is an applied science company building GPU-resident distributed data systems that deliver 10–100x performance for Fortune 500 clients including NVIDIA and Delta. We're Series B ($145M raised), ~70 people, headquartered in San Francisco with a New York office and our SV11 compute facility. Our stack runs on a 256-petaflop NVIDIA DGX cluster with NVL72 GPU infrastructure, combining Spiking Neural Networks, Graph Neural Networks, and causal inference to deliver real-time analytics that were previously impossible.The RoleWe're hiring a Senior Software Engineer onto our Applied AI team to build and extend the backend systems that power our platform. This is a hands-on role on a small team where your work ships to production quickly and directly shapes what our largest customers see. You'll work across Python-heavy backend services, data systems, and the infrastructure layer that connects them to our GPU-resident compute.A note on Applied AI. Our work is causal, not generative AI. The AI in Applied AI refers to the causal, graph-based, and neural systems our science team builds — and your job is to make them fast, reliable, and usable in production. If you're looking for prompt engineering or LLM fine-tuning work, this isn't the role. If you want to build serious backend systems that happen to serve some of the most interesting applied science work being done anywhere, read on.This is not a spec-in, spec-out role. You'll operate with ambiguity, make calls on tradeoffs, and partner directly with senior engineers and leadership on what to build and how.What You'll DoBuild production backend services in Python — APIs, data services, and the glue between our compute layer and the products customers useWork across the stack as needed — touch whatever part of the system the problem requires, from service code to data pipelines to integration layersShip iteratively against real customer needs — work directly with data products, science, and customer-facing teams to turn requirements into working systemsOwn what you build — take responsibility for reliability, performance, and evolution of the services you stand upRaise the bar for how we engineer — contribute to code quality, technical direction, and mentorship of earlier-career engineersWhat We're Looking ForMust-have5+ years of backend software engineering experience in production environmentsStrong Python fundamentals and experience building and operating backend servicesDemonstrated ability to work across adjacent parts of a stack (data, infrastructure, APIs) rather than staying in a narrow laneTrack record of shipping in fast-moving, ambiguous environmentsClear written and verbal communication — you can articulate tradeoffs, explain decisions, and collaborate across functionsShould-haveExperience designing and operating distributed systemsComfort with performance-sensitive code and systems where latency and throughput matterExposure to data-intensive applications — pipelines, storage systems, or analytical workloadsNice-to-haveGPU or accelerator-adjacent engineering experienceBackground in high-scale or high-performance computing environmentsExperience partnering closely with applied science or research teamsFamiliarity with causal inference or graph-based systemsWhy AlembicWork on systems that are genuinely novel — GPU-resident infrastructure running real-time causal computation at a scale few companies are attemptingCustomers who use the product seriously — NVIDIA, Delta, and others rely on what we buildSmall team, high ownership, short path from idea to productionFive days onsite in a downtown SF office with a team that cares about the craftCompensation Range: $211K - $235KLocationSan Francisco HQAddressSan Francisco, CaliforniaEmployment TypeFull timeLocation TypeOn-siteDepartmentApplied AICompensationIC5 SeniorOur compensation philosophy ensures new hires earn 50%+ current benchmarks. We'll discuss further with you. Most recent San Francisco benchmark data: $211K – $235K • Offers EquityOur Compensation Philosophy:Market-based: Our formula ensures new hires earn at or above real-time benchmarks. Ownership: Our generous equity program ensures new hires are owners, not just employees.Transparent: We openly discuss salary expectations to avoid surprises later in the process. Data-driven: We use objective data to remove bias and ensure consistency in compensation decisions.