---
title: 'Senior Applied AI Engineer at Alembic'
canonical: 'https://feeny.ai/job/senior-applied-ai-engineer-alembic-san-francisco-jh4y886w59at'
type: 'job'
last_seen: '2026-09-07'
---

# Senior Applied AI Engineer at Alembic

- **Company:** Alembic
- **Location:** San Francisco, CA
- **Compensation:** $211k–$235k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-23
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/alembic/66b22b80-faf3-45a6-a6c8-02472b3ee18c

## Job description

## 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 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 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

## WHY ALEMBIC

- Work on systems that are genuinely novel — GPU-resident infrastructure running real-time causal computation at a scale few companies are attempting
- Customers who use the product seriously — NVIDIA, Delta, and others rely on what we build
- Small team, high ownership, short path from idea to production
- Five days onsite in a downtown SF office with a team that cares about the craft

## About Alembic

## Company Overview
- **One-liner**: Alembic provides a real-time Causal AI platform that enables enterprises to measure, simulate, and optimize the true incremental impact of marketing investments on revenue.
- **Entity Type**: Private (Series B)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2018
- **Founders**: Not publicly available

## Core Business
- **Primary industry/industries**: Marketing analytics / Enterprise AI / Causal inference software
- **Target customers**: B2B – Fortune 500 enterprises, large B2C brands, and sophisticated marketing organizations
- **Mission or purpose statement**: To make blind, guess-based analysis obsolete by helping global enterprises act with clarity and confidence in the intelligence era.

## Products & Services
- **Alembic Causal AI Platform (3.0)**: A SaaS platform that continuously recomputes large-scale causal graphs across billions of signals (media exposure, pricing, macroeconomics, consumer behavior, operational inputs). Enables real-time budget simulation, marginal ROI analysis, incremental lift measurement, and scenario testing without batch processing.
- **Marketing Measurement & Attribution**: Replaces traditional MMM, MTA, and dashboards with dollar-for-dollar attribution across the full marketing funnel, isolating true causal impact per channel and tactic.
- **Enterprise Intelligence**: Extends causal inference beyond marketing to areas like pricing, sponsorship evaluation, and go-to-market strategy for cross-functional decision-making.

## Market Standing
- **Valuation/Market Cap**: $645 million (as of March 2026, per Techmeme)
- **Key Metric**: Total Funding – $145M Series B led by Prysm Capital and Accenture (March 2026); prior rounds include $16M Series A (WndrCo-led) and $2.6M Seed (KB Partners-led). Total disclosed funding approximately $128M–$145M.
- **Notable Investors/Partners**: Prysm Capital, Accenture, NextEquity, WndrCo, SLW, KB Partners. NVIDIA is the founding enterprise customer and exclusive supercomputing partner (first Causal AI company to secure NVIDIA DGX SuperPOD).
- **Growth Signals**: Headcount grew 76.6% year-over-year (to ~57 employees). Active job postings for engineering and applied AI roles. Multiple Fortune 500 clients (e.g., major airline, B2B tech firm) with measurable pipeline and revenue impact.

## Competitive Advantages
- **Causal AI vs. correlation**: Models cause-and-effect at scale, not just patterns; can simulate downstream impact of strategic decisions in real time.
- **Real-time graph architecture**: Continuously recomputes causal graphs instead of running batch reports, giving live views of incremental revenue drivers.
- **NVIDIA partnership**: Exclusive access to DGX NVL72 supercomputing infrastructure for enterprise decision-making, creating a hardware/software moat.
- **Proven enterprise traction**: Demonstrated pipeline growth of 37% for a Fortune 500 B2B client and precise sponsorship measurement for a major airline.

## Strategic Focus
- **Current priorities and direction for growth**: Expand causal AI applications beyond marketing into broader enterprise intelligence (pricing, operations, strategy). Scale platform adoption with Fortune 500 companies and deepen integrations with NVIDIA’s AI infrastructure. Continue hiring top AI research and engineering talent to advance causal inference capabilities.

## Why Work Here
- **Culture highlights**: Values include “embrace curiosity,” “be data driven,” “build stuff & ship it,” “maintain low egos,” “don’t blame, solve,” “everyone teaches,” and “brevity is strength.” Emphasis on experimentation, cross-department learning, and shipping without overanalysis.
- **Remote/hybrid/office policy**: In-person at San Francisco HQ (all open positions listed as “In Person Full Time”).
- **Notable perks or engineering culture**: Work on frontier Causal AI models with access to NVIDIA DGX SuperPOD. Opportunity to solve complex, high-impact problems for Fortune 500 clients. Flat, low-ego environment with a focus on shipping and data-driven decisions. Active open roles: Research Engineer – Causal AI, Senior Applied AI Engineer, Senior Site Reliability Engineer, Patent Counsel, Senior Field Scientist.

## Sources
1. [Alembic Website – Platform Overview](https://alembic.com/)
2. [Alembic – About Us & Culture](https://alembic.com/company)
3. [Alembic – Careers Page](https://alembic.com/careers)
4. [LinkedIn – Alembic Technologies Company Profile](https://www.linkedin.com/company/getalembic)
5. [Techmeme – Alembic raises $145M Series B at $645M valuation](https://www.techmeme.com/)
6. [Accenture Newsroom – Accenture Invests in Alembic](https://newsroom.accenture.com/)
7. [Alembic – Job Board (Ashby)](https://jobs.ashbyhq.com/alembic)

## Other roles at Alembic

- [Corporate IT Engineer](https://feeny.ai/job/corporate-it-engineer-alembic-san-francisco-r23xef67272p) — San Francisco, CA
- [Personal Trainer](https://feeny.ai/job/personal-trainer-alembic-san-francisco-5z7ydpcvkh3x) — San Francisco, CA
- [Technical Recruiter](https://feeny.ai/job/technical-recruiter-alembic-san-francisco-4n2tm5wcztb1) — San Francisco, CA
- [Technical Sourcer](https://feeny.ai/job/technical-sourcer-alembic-san-francisco-nn6tpm5b3zch) — San Francisco, CA
- [Senior Network & Site Reliability Engineer](https://feeny.ai/job/senior-network-site-reliability-engineer-alembic-san-francisco-mfdnj1j8nb1n) — San Francisco, CA
- [Patent Counsel](https://feeny.ai/job/patent-counsel-alembic-san-francisco-za6p9s63wmk8) — San Francisco, CA
- [Senior Field Scientist](https://feeny.ai/job/senior-field-scientist-alembic-san-francisco-5rspg70tzw49) — San Francisco, CA
- [Senior Site Reliability Engineer](https://feeny.ai/job/senior-site-reliability-engineer-alembic-san-francisco-dmmytp9nn6x1) — San Francisco, CA
- [Research Engineer - Causal AI](https://feeny.ai/job/research-engineer-causal-ai-alembic-san-francisco-ems0psx1gntj) — San Francisco, CA
- [Senior Applied AI Engineer](https://feeny.ai/job/senior-applied-ai-engineer-qualysoft-budapest-77yvp0pdmsm0) — Budapest, Hungary