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Senior Applied AI Engineer

Alembic · San Francisco HQ

onsitesenior$211,000–$235,000Posted Apr 23, 2026PythonAPIsDistributed SystemsData PipelinesCausal InferenceGraph Neural NetworksGPU/Accelerator

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About this role

**ABOUT ALEMBIC** Alembic 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 ROLE** We’re hiring a **Senior Software Engineer** to join 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** connecting them to our **GPU-resident compute**. > **Note on “Applied AI.”** Our work is **causal**, not generative AI. The “AI” refers to the **causal, graph-based, and neural systems** our science team builds—your job is to make them **fast, reliable, and usable in production**. If you’re looking for **prompt engineering** or **LLM fine-tuning**, this isn’t the role. --- **WHAT YOU’LL DO** - Build **production backend services in Python**: APIs, data services, and the glue between compute and customer-facing products - Work across the stack as needed—touch whatever part of the system the problem requires (service code, data pipelines, integration layers) - Ship iteratively against **real customer needs** with close collaboration across data products, science, and customer-facing teams - Own what you build: take responsibility for **reliability, performance, and evolution** of the services you stand up - Raise the bar for how we engineer: contribute to **code quality**, **technical direction**, and **mentorship** of earlier-career engineers --- **WHAT WE’RE LOOKING FOR** **Must-have** - **5+ years** of backend software engineering experience in production environments - Strong **Python** fundamentals and experience building/operating backend services - Demonstrated ability to work across adjacent parts of a stack (**data, infrastructure, APIs**) - Track record of shipping in **fast-moving, ambiguous** environments - Clear written and verbal communication—able to articulate tradeoffs, explain decisions, and collaborate across functions **Should-have** - Experience designing and operating **distributed systems** - Comfort with **performance-sensitive** code and systems where **latency/throughput** matter - Exposure to **data-intensive applications** (pipelines, storage systems, analytical workloads) **Nice-to-have** - GPU or accelerator-adjacent engineering experience - Background in **high-scale** or **high-performance computing** environments - Experience partnering closely with **applied science** or **research** teams - Familiarity with **causal inference** or **graph-based** systems --- **WHY ALEMBIC** - Work on systems that are genuinely **novel**: GPU-resident infrastructure running **real-time causal computation** at a scale few companies attempt - Customers who use the product seriously (e.g., **NVIDIA**, **Delta**) - **Small team**, high ownership, short path from idea to production - **Five days onsite** in a downtown SF

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