Applied AI Engineer

Rowspace; New York (NY); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and vision insurance

401(k) plan with employer match

Monthly commuter stipend

Free daily lunch

Fully stocked snack bar

Job summary

Rowspace is seeking an Applied AI Engineer to enhance their financial insight platform. You will leverage your expertise to build systems that interpret financial data, implement advanced AI techniques, and produce reliable systems tailored to customer feedback.

The ideal candidate should have over 3 years of experience in machine learning and a strong background in AI research and LLMs. Rowspace offers comprehensive benefits including medical insurance and a 401(k) plan.

Qualifications

• 3+ years of experience in machine learning or AI engineering.
• Strong background in LLMs and RAG systems.
• Experience designing evaluation frameworks for AI systems.

Responsibilities

• Implement and adapt AI research to build systems for understanding financial context.
• Design retrieval pipelines to extract insights from unstructured data.
• Construct and maintain knowledge graphs for financial relationships.

Skills

Machine learning

AI research

Applied AI engineering

LLMs

Retrieval systems

Entrepreneurial mindset

Tools

React

Typescript

Python

Node

Job description

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
• Strong background in LLMs, RAG systems, and agentic AI workflows
• Experience designing evaluation frameworks and benchmarks for AI systems
• Interest or understanding of financial markets, investment processes, or quantitative finance (or strong interest in learning)
• Experience with retrieval systems, embeddings, and multi-modal data processing
• Publication record or demonstrated expertise in relevant AI research areas is a plus
• Entrepreneurial mindset with ability to translate cutting‑edge research into practical business value
• Experience as a full‑stack engineer is a plus (React/Typescript + Python/Node or similar)

Perks & Benefits

• Health & Wellness: Comprehensive medical, dental, and vision insurance
• Future Planning: 401(k) plan including employer match on contributions made while employed by Rowspace
• Food & Fuel: Monthly commuter stipend, plus free daily lunch and a fully stocked snack bar in the office
• Team Culture: Regular team offsites to bond and strategize away from the desk