The Role

As an Applied AI Engineer, you'll bring the frontier of AI research and engineering to Rowspace, transforming how our platform understands and surfaces critical financial insights. In a typical week, you might build and productionize an agent in response to customer feedback, design evaluation frameworks for AI performance, and implement advanced retrieval systems to make the most of AI for finance workflows.

What You'll Do

Implement and adapt cutting-edge AI research to build systems that understand financial context and business concepts
Design retrieval pipelines that extract and synthesize insights from unstructured sources (PDFs, emails, presentations) with intelligent conflict resolution
Build agentic workflows that enable AI systems to reason about financial relationships, perform benchmarking, and conduct comparative analysis
Construct and maintain knowledge graphs that capture complex financial relationships, entity connections, and market dynamics
Create evaluation frameworks to measure and improve AI performance across investment research, due diligence, and portfolio monitoring tasks
Design and implement systems that maintain traceability from AI outputs to primary sources
Experiment with the latest LLM orchestration patterns and context management techniques for financial use cases
Shape technical direction and best practices for AI application development at Rowspace
Iterate rapidly with direct customer input, continuously refining AI systems based on real-world usage and feedback
Deploy and operate production systems end-to-end, with strong ownership over reliability, performance, and maintainability across the stack

What You Have

3+ years of experience in machine learning, AI research, or applied AI engineering

The best investors we know have built something over years and decades that's impossible to replicate: institutional memory of how they think and operate. It lives in memos, models, investment committee notes, emails, deal history, and trading data — scattered across systems that hold the patterns of what worked, what didn't, and why. That accumulated knowledge and how they apply it is their edge.

The problem is, it's trapped. It's messy and conflicting. It's locked behind stringent security and compliance controls. And most AI tools can't extract its meaning, much less scale it. That's the challenge we're taking on at Rowspace.

The firms we speak to know they need to drive AI transformation on an aggressive timeline. We've seen close up that AI is useless without the right data to act on. With public data increasingly commoditized, maintaining your edge demands a way to scale the judgment and insight latent in all the proprietary data your firm possesses.

Rowspace is launching to provide exactly this: specialized intelligence for investors to make faster, sharper decisions. We're thrilled to do it with $50M in backing from Sequoia, Emergence, Stripe, Conviction, Basis Set, Twine, and angels from across finance.

Applied AI Engineer

About the role

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