The Role

This role sits at the intersection of data engineering, ML systems, and product development. You’ll design and maintain the pipelines, models, and integrations that turn messy, real-world financial systems into clean, reliable, AI-ready data products.

You won’t be training foundation models — but your work will directly determine whether our AI systems can reason correctly, produce trustworthy insights, and scale across customers.

If you enjoy building robust data systems that real products depend on — and care deeply about correctness, observability, and long-term scalability — this role is for you.

What You’ll Do

• Design, build, and maintain scalable data pipelines (ETL / ELT) across customer systems

• Own integrations with financial and operational tools (e.g. accounting, billing, ERP, CRM)

• Model and transform raw data into clean, well-defined analytical and AI-ready datasets

• Build and maintain data products that power AI reasoning and insights

• Ensure data correctness, consistency, and lineage across customers and entities

• Implement data quality checks, validation, and monitoring

• Collaborate closely with AI engineers to support RAG, GraphRAG, and agent workflows

• Design systems that support multi-entity, multi-subsidiary financial data

• Optimize for performance, scalability, and cost as data volumes grow

• Help define best practices around data modeling, transformations, and reliability

• Participate in architectural decisions and cross-functional technical discussions

What We’re Looking For

Core Data & Systems Experience

• 6–10+ years of experience in data engineering, ML systems, or backend-heavy engineering roles

• Strong experience designing and operating production data pipelines

• Deep understanding of relational data modeling (PostgreSQL or similar)

• Experience with ETL / ELT patterns and tools

• Experience integrating external systems and APIs

• Strong SQL skills and comfort working with complex datasets

• Experience working on cloud platforms (ideally GCP)

• Familiarity with infrastructure-as-code and CI/CD practices

ML & AI Context

• Experience supporting ML or AI-powered products in production

• Understanding of how data quality impacts model behavior and AI outputs

• Familiarity with feature pipelines, embeddings, or analytical datasets used in AI systems

• Pragmatic mindset around correctness, explainability, and failure modes

You don’t need to be an AI researcher — but you do need to understand how your data will be used by AI systems.

Mindset & Way of Working

• High ownership, strong bias to action — you default to shipping, iterating, and fixing problems end-to-end

• Product-minded engineer — you care deeply about the user experience and business impact, not just technical elegance

• Comfortable with ambiguity — you thrive in early-stage environments without perfect requirements or heavy process

• Strong opinions, loosely held — you bring conviction, but are pragmatic and adaptable

• Scrappy and self-directed — you’re energized by building from zero to one and wearing multiple hats

• Clear, direct communicator — you collaborate effectively in small, senior teams

• Low ego, high fun — you’re humble, kind, and enjoy building with others

• In-person oriented — you value working together face-to-face several days a week

If you’re looking for a highly structured, process-heavy, corporate engineering environment, this role is probably not a good fit.

Nice to Have

• Previous experience as a founding engineer or early employee at a startup (especially in B2B SaaS), demonstrating ability to build from scratch and adapt quickly

• Prior exposure to financial systems or Office of the CFO domains (e.g. FP&A, accounting, business analytics).

What We Offer

• The opportunity to build a category-defining product for CFOs and finance teams, tackling important problems in a huge industry.

• Deep, hands-on exposure to applied AI systems in a real production environment (this is a chance to push the state-of-the-art in practice, not just in theory).

• A high-trust, senior team with strong technical taste and a collaborative, low-ego culture. You’ll be working with humble but world-class talent that values learning and growth.

• Real ownership and influence over architecture and product direction – your ideas will shape the product and company.

• Competitive compensation, startup equity, and benefits.

• A hybrid work setup with flexible remote scheduling and intentional in-person collaboration. (We have a coworking space and get together ~2-3 days a week to whiteboard, pair program, and have fun as a team.)