Founding AI Engineer

Responsibilities

• Design, build, and operate RAG and agentic systems over complex financial data
• Develop scalable backend services for document processing, async job queues, and risk scoring
• Own the productionization of AI systems, including evaluation pipelines and safe rollout strategies
• Harden the platform for enterprise-grade security, including auth controls, audit trails, and monitoring
• Establish CI/CD, deployment pipelines, and incident response practices from the ground up
• Work directly with the founding team to define architecture, technical roadmap, and product direction

Requirements

• 1+ years of technical experience, with startup experience strongly preferred
• Strong proficiency in TypeScript and Python
• Hands-on experience shipping LLM integrations or RAG systems into production
• Experience with document processing, entity extraction, and structured data extraction
• Solid grasp of API design, relational databases, and async job processing systems
• Proven track record of taking products from local development to reliable production scale

Preferred Qualifications

• Knowledge of KYC/KYB/AML workflows or regulated fintech
• Experience with LangChain, LlamaIndex, or similar AI orchestration frameworks
• Familiarity with OCR and document intelligence pipelines
• Background in fintech, compliance, or RegTech
• Cloud deployment experience and DevOps knowledge in security-sensitive environments

Benefits

• Competitive salary and equity
• 100% health, dental, and vision coverage
• Commuter stipend
• Regular team events and off-sites

About the Company

Manhattan Labs is building an AI-native compliance platform for community banks and financial institutions. We are creating the intelligence layer that automates complex regulatory workflows through agentic reasoning and advanced RAG systems. Our team includes researchers and engineers from Stanford and Carnegie Mellon, backed by Tier 1 investors.