_{Forward Deployed Engineer / Applied AI Engineer}

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_{Our client is a rapidly scaling company in the AI + financial services space, building the future of audit with Agentic AI. Backed by Lightspeed Venture Partners,  they are acquiring and modernizing CPA firms to transform financial audits from the ground up.}

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_{Audits today are slow, manual, error-prone, and built on decades-old tooling. They are changing that. As they deploy their first firm acquisition and expand engineering, they’re looking for a Forward Deployed / Applied AI Engineer who can operate in real customer environments, bring structure to messy financial data, and ship production-grade AI systems that directly drive revenue, trust, and accuracy.}

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_{This is a role for someone who loves building in the real world — fast iteration, real users, hands-on debugging, and ownership over zero-to-one applied AI systems.}

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_{What You’ll Do}

_{- Build and deploy AI agents that parse financial documents, extract entities, reconcile numbers, and complete audit workflows end-to-end}

_{- Work across the entire stack: Python backends, LLM pipelines, RAG systems, vector stores, browser automation, internal tools, and integrations}

_{- Design, own, and scale zero-to-one systems for document processing, pipeline orchestration, and real-time agent execution}

_{- Ship quickly, iterate rapidly on v1s, collect user feedback, and compound wins through continuous improvement}

_{- Partner directly with early customers and founders, ensuring agents ship to production and deliver measurable business outcomes}

_{- Evaluate, test, and integrate emerging AI frameworks, agent toolchains, and LLM best practices}

_{- Contribute to engineering culture, infrastructure decisions, and standards for reliability, observability, and velocity}

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_{What They’re Looking For}

_{- 3+ years of experience building and shipping backend, AI, or infra systems in production}

_{- Strong Python engineering skills with a bias toward fast iteration and ownership}

_{- Experience or interest in LLMs, agentic frameworks, browser automation, RAG pipelines, or document parsing}

_{- Comfort designing systems around real-world, messy data and tight feedback loops}

_{- Ability to communicate clearly with customers, founders, and cross-functional teams}

_{- Strong debugging instincts, not afraid to fix data pipelines, write scrapers, or jump into production logs}

_{- Entrepreneurial, proactive mindset: you take initiative, move quickly, and thrive in ambiguity}

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