Applied AI Engineer

Sapien

$120K — $160K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in machine learning and AI systems development
  • Strong algorithmic thinking demonstrated through ML research or competitive programming
  • Experience with agent frameworks and large language models (LLMs)
  • Proven ability to work from research to production deployment
  • Familiarity with modern programming languages and data structures

Responsibilities

  • Design and implement agent architectures for financial workflows
  • Build systems that learn from customer interactions to enhance efficiency
  • Create graph-based representations for improved data searching
  • Develop multi-modal parsers for diverse financial data integration
  • Establish benchmarking suites to measure system performance and impact

Benefits

  • Flexible work hours to support work-life balance
  • Opportunities for professional development and growth
  • Collaborative and innovative work environment
  • Work with a mission-driven team focused on impactful AI solutions
  • Access to cutting-edge technology and resources
Full Job Description
The role

You'll build the AI agent capabilities that power Sapien's autonomous finance operations. This means designing novel architectures for reasoning over complex financial data, implementing verifiable and observable agent workflows, and building systems that learn and adapt to each company's unique operations.

This is a research-meets-product role. You'll work on cutting-edge agent capabilities-from observability and library learning to semantic search and multi-modal parsing-and ship them directly into production for customers.

What you'll do
  • Design and implement agent architectures that enable observability, human-in-the-loop verification, and precise context control across complex financial workflows.
  • Build library learning systems that reduce LLM dependencies by learning reusable patterns for planning, code generation, and data localization from customer interactions.
  • Create graph-based company representations and develop efficient search methods using embeddings, semantic clustering, and custom retrieval strategies.
  • Build multi-modal parsers that unify diverse financial data sources (Excel, ERPs, CRMs) into coherent, queryable schemas that agents can reason over.
  • Design benchmarking and evaluation suites that quantify Sapien's accuracy, reliability, and business impact across different customer workflows.
What we're looking for
  • Strong algorithmic thinking. Demonstrated through ML research, competitive programming, mathematics, or building novel systems from scratch.
  • Experience with modern agent frameworks, LLMs, and AI systems: fine-tuning, retrieval augmentation, tool use, or agentic architectures.
  • Comfort working end-to-end: from implementing research ideas and prototyping architectures to deploying production systems and iterating on real customer feedback.
How you work (values we care about)
  • Adaptability: You thrive on diverse, open-ended problems. One day you're implementing a new agent architecture, the next you're debugging a customer data issue-and you bring the same intensity to both.
  • Ownership: You take problems from research paper to production. You don't wait for direction-you identify what needs to happen and drive it to completion.
  • Opinionated: You have strong technical perspectives on what works and what doesn't. You push back on approaches you disagree with and make the team's thinking sharper.
  • Mission-driven: You're energized by building AI that transforms how businesses run. You connect technical decisions to real customer outcomes and care deeply about the impact.
  • Collaborative excellence: You share knowledge, give thoughtful feedback, and invest in making the team better. You bring new ideas from papers and discussions to elevate everyone's thinking.

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