Alembic
Senior Applied AI Engineer
San Francisco HQ · Senior
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About the role
- 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.
Responsibilities
- Own what you build - take responsibility for reliability, performance, and evolution of the services you stand up
- Strong Python fundamentals and experience building and operating backend services
- 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.
Requirements
- 5+ years of backend software engineering experience in production environments
- Demonstrated ability to work across adjacent parts of a stack (data, infrastructure, APIs) rather than staying in a narrow lane
- Track record of shipping in fast-moving, ambiguous environments
- Experience designing and operating distributed systems
- Comfort with performance-sensitive code and systems where latency and throughput matter
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
- Work on systems that are genuinely novel - GPU-resident infrastructure running real-time causal computation at a scale few companies are attempting
- Small team, high ownership, short path from idea to production
Compensation
- $10k-$100k
Company info
- Build production backend services in Python - APIs, data services, and the glue between our compute layer and the products customers use
- Work across the stack as needed - touch whatever part of the system the problem requires, from service code to data pipelines to integration layers
This listing is sourced directly from Alembic's careers page and normalized into a canonical job model.