# Senior Applied AI Engineer

**Company:** [Alembic](https://hotfix.jobs/companies/alembic-2)
**Location:** San Francisco, CA
**Role:** Backend Engineering
**Salary:** $182k – $207k/yr
**Experience:** 5+ years
**Skills:** Python, Distributed Systems, APIs, Data Pipelines, GPU, High-Performance Computing, Causal Inference, Graph-Based Systems, Backend Services, Performance Optimization
**Posted:** 2026-04-23

> Builds and maintains Python backend services, APIs, data pipelines, and infrastructure integrating GPU-resident compute for causal AI analytics platform. Requires 5+ years backend experience, ability to ship in ambiguous environments, and work across stack for production reliability.

## Job Description

## What You'll Do
- 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
- Ship iteratively against real customer needs — work directly with data products, science, and customer-facing teams to turn requirements into working systems
- 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 and operating backend services
- 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
- Clear written and verbal communication — you can 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 and throughput matter
- Exposure to data-intensive applications — pipelines, storage systems, or 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

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