Senior Applied AI Engineer
About The Position
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.
Requirements
- 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
Nice To Haves
- 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
Responsibilities
- 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
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
