Job Description

Who is Recruiting from Scratch
Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.
Title of Role: Senior Applied AI Engineer
Location: San Francisco, CA (On-site, 5–6 days/week)
Company Stage of Funding: Series A (~$37M raised, led by Lightspeed)
Office Type: On-site
Salary: $250,000 – $400,000 + Significant Equity (~$700K+ potential value)
Visa: Visa sponsorship available (H1B, O-1, TN, E-3, STEM OPT, transfers supported)

Our client is building enterprise-grade AI agent systems that automate financial audits for public companies.

Their mission is to enable AI systems to interpret complex, unstructured financial data (PDFs, Excel files, reports, and enterprise systems) and perform high-stakes reasoning over it—replicating and augmenting the decision-making processes of CFOs and audit teams at Fortune 500 companies.

The company is tackling one of the hardest applied AI problems today: building reliable agents that operate over noisy, out-of-distribution financial data at massive scale.

Backed by top-tier investors (Lightspeed and others), they are already closing major enterprise contracts and scaling aggressively from ~8 → 30+ employees.

This is a rare opportunity to build frontier AI agent systems in a high-stakes, production-critical enterprise environment.

What You Will Do

• Design and build autonomous AI agent systems for financial audit workflows
• Architect agent reasoning systems (planning, memory, tool use, recovery)
• Build production-grade pipelines for processing large-scale structured + unstructured financial data
• Develop distributed systems for handling 100GB+ enterprise datasets
• Improve agent reliability in high-stakes decision environments
• Debug complex multi-step agent failures in production systems
• Build evaluation frameworks for reasoning accuracy and audit correctness
• Design feedback loops to improve agent performance over time
• Work on document intelligence systems (PDFs, Excel, financial filings)
• Optimize system performance across latency, cost, and reliability constraints
• Translate frontier AI research into production-grade enterprise systems
• Own architecture decisions end-to-end across backend + AI systems

Ideal Candidate Background

• 4–8+ years of experience in software engineering or applied AI systems
• Strong Python + TypeScript experience
• Proven experience building production AI systems or agentic workflows
• Strong distributed systems or backend engineering background
• Experience working with unstructured or enterprise data
• Startup or high-growth company experience (Series A–D preferred)
• Strong systems thinking and ability to operate in ambiguous environments
• Comfortable owning end-to-end system design and execution
• Strong product intuition and ability to work closely with non-technical stakeholders

Preferred Experience

• AI agent systems (planning, memory, tool use)
• LLM applications in production environments
• Distributed data processing systems
• Financial or enterprise data systems
• Open-source AI agent frameworks
• Experience at high-quality engineering orgs (Ramp, Stripe, Brex, Databricks, etc.)
• Research-to-production AI transitions
• Strong backend + infra fundamentals

Strong Signals

• Built AI agents in production environments
• Owned complex backend + AI systems end-to-end
• Experience with enterprise-grade data pipelines
• High ownership in early-stage startups
• Experience at top-tier applied AI or infra companies
• Clear trajectory of increasing scope/impact
• Strong engineering fundamentals + systems intuition

Compensation and Benefits

• Base salary: $250,000 – $400,000
• Equity: ~ $700K in value (high upside early-stage equity)
• Full visa sponsorship available
• High ownership from day one
• Direct founder-level technical exposure
• Work on frontier AI agent systems in enterprise finance

Why Join

This is a rare opportunity to build the foundational AI systems that will redefine how financial audits are performed globally.

You will be working on some of the most technically complex applied AI problems today—where correctness, reliability, and reasoning quality matter at enterprise scale.

If you want to work at the intersection of LLMs, distributed systems, and real-world financial decision-making, this is a high-impact, high-ownership role with exceptional upside.