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Staff AI Engineer

Kastle — AI agents for mortgage servicing

San Francisco Senior+ $250K – $350K • Offers Equity Posted Nov 22, 2025
PythonREST/APIsAI/LLMML

About the role

ABOUT KASTLE

Kastle is building the AI employee for consumer lending. We work with some of America's largest banks and mortgage lenders, helping them scale their contact center and compliance operations using autonomous AI Agents that process payments, originate loans, and help customers get a world class experience during the biggest financial decisions of their lives. We've processed over $1 billion in transactions and are backed by Y Combinator and Commerce Ventures. If you are interested in building AI that is applied in the real world where precision, reliability, and performance matter and redefine access to credit across the world, apply below.

ABOUT THE ROLE

As a Founding Applied AI Engineer, you'll be instrumental in building the technical foundation of Kastle's AI platform. You'll fine-tune large language models, design AI workflows for highly regulated enterprises, and ensure our voice agents deliver precise, compliant, and effective borrower interactions.

This role is ideal for an engineer who is passionate about applied AI, eager to solve real-world challenges, and excited to build the technical foundation of an early-stage AI startup.

WHAT YOU'LL DO

- AI Model Integration: Fine-tune and deploy LLMs for real-time voice-based borrower interactions

- Prompt Engineering: Design and iterate on prompt strategies to optimize AI performance and compliance

- Evaluate LLMs and AI Agents: Build high quality evals using our proprietary datasets to benchmark AI agent performance and run experiments

- Custom AI Solutions: Train and implement domain-specific AI models for consumer lending

- Scalability & Compliance: Ensure AI solutions meet regulatory standards (FDCPA, RESPA, TILA) and scale efficiently

- Data Pipelines & APIs: Build robust AI-driven workflows that integrate seamlessly with loan servicing platforms

- Continuous Optimization: Monitor performance metrics and continuously improve agent quality and borrower experience

WHAT WE'RE LOOKING FOR

- 3+ years building and deploying ML/AI systems in production environments

- Strong proficiency in Python and deep learning frameworks (TensorFlow, PyTorch)

- Experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)

- Track record of shipping end to end AI systems that is at the core of company operations

- Strong product mindset and ability to translate business requirements into AI solutions

- Excellent communication skills to collaborate across product, engineering, and compliance teams

WHY JOIN KASTLE

- Opportunity to work with a world class team building a generational AI company that will redefine how every loan in America is made and managed

- Ability to move fast while your work impacting millions of customers. Add a new feature in a few days and ship it to top 10 lenders the next week.

- Competitive Compensation + Meaningful Equity at a high growth company

- High ownership and direct input on product direction, company culture, and how the FDE function scales

Other Perks and Benefits

- Free Health and Wellness Membership

- Robust medical, vision, & dental coverage

- 401(K) plan offering

- Paid Company Meals

- Company offsites to get to know the team

What the index says about this role

  • First seen by JobLarper — Aug 2, 2026, 6 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
  • What Machine Learning Engineer roles ask for — across 1,108 indexed openings: ML (78%), AI/LLM (55%), Python (53%), REST/APIs (38%), Cloud (25%). This posting names ML, AI/LLM, Python, REST/APIs.
  • Kastle is hiring actively — 6 open roles indexed.

Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.

⚡ JobLarper watched this role appear on Kastle's official board on Nov 22, 2025. Sign up free to get alerted minutes after roles like this go live, and tailor your real résumé to the exact description — nothing invented.

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