Strativ Group
San Francisco (Hybrid)
Founding/Staff Engineer
$200-300k base
Our client is an
AI-native research and product lab
on a mission to
redefine how global finance operates . Backed by a team that includes former
Google DeepMind researchers and engineers , they are applying frontier AI to some of the most complex, high-stakes problems in finance.
This is a true
founding engineer
opportunity. Youll help turn cutting-edge AI research into
production systems used by real financial institutions , while shaping the technical foundation, standards, and culture from the ground up.
What youll do Build core product features end-to-end , spanning frontend, backend, and infrastructure using TypeScript, React, and Node.js. Productionize frontier ML research , working closely with researchers to ship robust, user-facing AI systems. Design and own critical services , architecting reliable, scalable infrastructure with Docker and Kubernetes. Set the engineering bar
as a founding team memberestablishing standards for code quality, testing, and development workflows. Prototype rapidly, ship decisively, and iterate continuously , collaborating closely with product managers, designers, and researchers. Make thoughtful architectural decisions, including
rewriting systems when it meaningfully improves long-term quality and simplicity .
The ideal candidate:
Have built
polished, high-performance web applications
end-to-end, from design through production deployment. Are deeply fluent in
modern frontend development , including TypeScript, React, Tailwind, and Next.js. Can comfortably
design and evolve backend microservices
(Node.js or Python) to deliver features end-to-end. Are an expert in
at least one statically typed language
and have strong instincts around type safety, maintainability, and correctness. Have experience deploying production systems with
Docker and Kubernetes
on GCP Use AI as a productivity multiplierbut
critically evaluate AI-generated code , catching bugs and calling out poor design. Thrive in a
high-performance, high-ownership environment
alongside other strong engineers. Enjoy tackling technically deep, ambiguous problems and thinking carefully about product tradeoffs.
Nice to have: Experience working with
ML or applied research teams , or familiarity with ML pipelines. Background in
fintech, trading, quant platforms, or other high-stakes domains . Prior experience as an
early-stage or founding engineer .
Our client is an
AI-native research and product lab
on a mission to
redefine how global finance operates . Backed by a team that includes former
Google DeepMind researchers and engineers , they are applying frontier AI to some of the most complex, high-stakes problems in finance.
This is a true
founding engineer
opportunity. Youll help turn cutting-edge AI research into
production systems used by real financial institutions , while shaping the technical foundation, standards, and culture from the ground up.
What youll do Build core product features end-to-end , spanning frontend, backend, and infrastructure using TypeScript, React, and Node.js. Productionize frontier ML research , working closely with researchers to ship robust, user-facing AI systems. Design and own critical services , architecting reliable, scalable infrastructure with Docker and Kubernetes. Set the engineering bar
as a founding team memberestablishing standards for code quality, testing, and development workflows. Prototype rapidly, ship decisively, and iterate continuously , collaborating closely with product managers, designers, and researchers. Make thoughtful architectural decisions, including
rewriting systems when it meaningfully improves long-term quality and simplicity .
The ideal candidate:
Have built
polished, high-performance web applications
end-to-end, from design through production deployment. Are deeply fluent in
modern frontend development , including TypeScript, React, Tailwind, and Next.js. Can comfortably
design and evolve backend microservices
(Node.js or Python) to deliver features end-to-end. Are an expert in
at least one statically typed language
and have strong instincts around type safety, maintainability, and correctness. Have experience deploying production systems with
Docker and Kubernetes
on GCP Use AI as a productivity multiplierbut
critically evaluate AI-generated code , catching bugs and calling out poor design. Thrive in a
high-performance, high-ownership environment
alongside other strong engineers. Enjoy tackling technically deep, ambiguous problems and thinking carefully about product tradeoffs.
Nice to have: Experience working with
ML or applied research teams , or familiarity with ML pipelines. Background in
fintech, trading, quant platforms, or other high-stakes domains . Prior experience as an
early-stage or founding engineer .