Fluency is enabling the autonomous Enterprise.
You're needed to help pioneer a new software category that will change how enterprises work. Welcome to the data layer of the future.
Fluency is looking for a next-level data engineer to build the data infrastructure the ontologizes how work happens across Fortune 500 organizations.
You'll be working on problems that have *no established solutions*. We're processing terabytes of workflow data per enterprise customer in real-time - systems that map, relationship, contextualize, and analyze work patterns across entire orgs. Think human genome project, but for enterprise workflows.
You'll invent new data primitives and paradigms. This means designing novel data structures for representing work, building pipelines that process billions of events per day, and writing whitepapers on approaches that don't exist yet.
You're operating at the bleeding edge of data science where the playbook hasn't been written.
We're backed by T1 VCs like Accel and are hitting an inflection point with Enterprises all around the globe.
You'll work directly with founders and our engineering team. The technical challenges are unprecedented: real-time processing at massive scale, creating a universal taxonomy for work across every industry, and building systems that can handle the most complex enterprise data environments on earth.
About the Role
We're looking for someone with:
- Strong programming knowledge, Python preferred
- Software engineering fundamentals - APIs, backend services
- SQL + DBT (or SQLMesh) proficiecy
- Infrastructure as code: Terraform (or equivalent)
- Orchestration: Dagster/Airflow/Prefect
- Production postgres experience
- Datalake experience (Iceberg, Databricks, etc)
- Computer Science Background - with caveat.
*If you don't have a CS background, you're challenged to beat one of the founders in a 1:1 whiteboard duel on DS&A judged by Hung. Neither founders have formal CS background, but come prepped.
There will be an expectation to stay up to business context, which could involve:
- Watching key customer calls
- Interacting with customers!
- Helping with product thinking
Strongly Preferred
- Has trained models before (even personal projects count, perhaps especially)
- You have interesting personal projects
- Pytorch or similar framework experience
- Kubernetes
- Ray for distributed compute
- Understand ML/DL systems from an infra perspective
- Deep learning theory understanding
- Esoteric knowledge
Our Customers
We work with some of the world’s largest:
- Financial services enterprises (Aon)
- Manufacturing enterprises (Misumi)
- And many more across the enterprise spectrum (PVH)
Our Culture
You're expected to be in love with the craft. You're expected to like laughing. You're expected to want to work on novel problems. You're expected to find satisfaction in novelty. You're expected to solve under obscurity.
Our Values
- In hesitation lies destruction; in action, glory.
- Those who merely meet expectations abandon the pursuit of greatness.
- One who dwells within the forum must regard it as hallowed ground.
- One who has not tasted the grapes declares them sour.
- One who sits alone at the feast misses the richness of the table.
Location
Full-time, in-person role based in San Francisco, CA.
- We offer E3 sponsorship for Australians to relocate with stipend
Compensation
- US$150K - $250K salary, depending on candidate and experience
- Substantial equity - every offer includes ownership
- Mac, Linux, or Windows - your call
- High-impact work with global enterprises
- Technical, product-led founders
Don't apply if:
- You want hybrid or remote
- You don't like working hard and with insane velocity
- You want to work a 9 -> 5
- You’re not comfortable with rapid iteration
- You prefer working on CRUD apps
- You don’t have personal projects
- You dislike AI
- You aren’t ambitious
Hiring Process
- Resume screen
- 1:1 with founder
- Interview w/ engineering team
- Work through something with the team
- Offer
We strongly encourage applicants from underrepresented backgrounds to apply. Diverse teams build better products — see value #5.
