Our client is an elite applied AI research and product lab focused on building AI-native systems for finance and deploying cutting-edge models into real production environments. Their work navigates the critical interface of data, research, and high-stakes financial decision-making.
As a Founding Data Engineer, you will take charge of the data platform that powers all operations: models, experiments, and user-facing products essential for demanding financial clients. You'll be instrumental in making foundational architectural decisions, collaborating closely with researchers and product engineers, and defining the data strategy from the ground up.
What you'll do:
• Design and implement the core data platform for ingesting, transforming, and delivering large-scale financial and alternative datasets.
• Collaborate with researchers and ML engineers to develop production-quality data and feature pipelines essential for cutting-edge models.
• Establish data quality, observability, lineage, and reproducibility for both experimental and production workloads.
• Deploy and manage data services using Docker and Kubernetes in a modern cloud setup (AWS, GCP, or Azure).
• Make key decisions on tools, architecture, and best practices to shape the company's data ecosystem.
• Continuously refine and evolve systems by simplifying or rewriting pipelines when necessary for long-term benefits.
Ideal candidate:
• Have built or managed high-performance data systems end-to-end, directly supporting production applications and ML models.
• Possess strong skills in backend and data infrastructure, with sufficient frontend knowledge for seamless product integration.
• Can design and enhance backend services and pipelines (Node.js or Python) to adapt to new product features and research tasks.
• Are proficient in at least one statically typed language, emphasizing type safety, correctness, and maintainability.
• Have experience in deploying data workloads and services using Docker and Kubernetes on major cloud platforms.
• Are comfortable making tough decisions, including simplifying, refactoring, or rebuilding legacy pipelines for quality and scalability.
• Leverage AI tools to enhance productivity while rigorously validating AI-generated code to ensure robust system design.
• Thrive in a high-expectation, high-responsibility environment alongside other exceptional engineers.
• Enjoy tackling complex challenges in data infrastructure, distributed systems, and performance.
Nice to have:
• Experience working with financial data (market, risk, portfolio, transactional, or alternative datasets).
• Familiarity with ML infrastructure, including feature stores, experiment tracking, or model serving systems.
• A background in a high-growth startup or foundational infrastructure role.
Compensation & setup:
• Competitive salary and founder-level equity
• Hybrid role based in San Francisco, promoting close collaboration and substantial ownership.
• Join a small, elite team dedicated to building core infrastructure with significant impact.
Founding Data Engineer role, San Francisco (Hybrid): $200-300k base.
