Applied Compute
1 open Forward Deployed Engineer role at Applied Compute. Curated with comp bands.
On the board since Jul 2026 · still hiring
Our take
Why Applied Compute
Three ex-OpenAI researchers selling the FDE motion itself — embedding is the product, not the support function.
- FDE type
- True forward-deployed
- Travel
- Medium
- Comp
- Undisclosed
- Stage
- Early-stage
A good fit if you're…
- Research-leaning engineers who want embedding as the core product
- People fluent in fine-tuning and agent training on enterprise data
- Candidates who want frontier pedigree at founding stage
What they do
Applied Compute was founded by three ex-OpenAI researchers to build custom AI agents trained on customers' own data. It raised $80M from Benchmark, Sequoia, Lux, and Elad Gil, and has been reported in talks at a $1.3B valuation — with Cognition, DoorDash, and Mercor among early customers.
What “forward deployed” means here
Here the embedding is the product: forward-deployed engineers sit inside enterprises to build and train bespoke agents on proprietary data, not to bolt on a generic model. The deployment work and the core offering are the same thing.
Comp & leveling
Comp is undisclosed, but founder pedigree, a Benchmark/Sequoia cap table, and $1.3B-range valuation talks point to a competitive, equity-heavy founding package. Expect the upside to sit in stock priced against a fast-rising mark.
Growth signals
Going from an $80M round to $1.3B valuation talks within months, with real enterprise logos already live, marks Applied Compute as one of the fastest-marked FDE-native startups on the board.
Analysis updated 2026-09-04
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