Founding AI Engineer - Build AI-Native Compliance Platform

Praxis, Inc.; San Francisco (CA); On-site; USD 140,000 - 220,000; Full time

Benefits offered by this job

Competitive salary and equity

Health, dental, vision coverage

Commuter stipend

Regular team events and off-sites

Job summary

Manhattan Labs, in San Francisco, is seeking a founding engineer to architect and build an AI-native platform for regulatory compliance. You’ll shape the system, own critical technical decisions, and partner with the founding team to push our enterprise-ready vision from MVP to production.

You’ll design agentic reasoning, large-scale document ingestion, and user-facing tools while ensuring regulatory scrutiny and reliability for financial institutions.

Qualifications

• 1+ years of experience on technical projects with startup experience strongly preferred
• Strong TypeScript and Python skills across modern frontend and backend stacks
• Hands-on experience shipping LLM integrations or RAG systems into production user-facing products
• Experience with document processing, entity extraction, and structured data extraction from messy real-world sources
• Solid grasp of API design, relational databases, and async job processing systems
• Proven track record taking a product from "works locally" to reliable production at growing scale
• Debugging instincts across frontend, backend, infra, and data boundaries - and an ownership mindset to match

Responsibilities

• Design, build, and operate RAG and agentic systems over complex financial data, with clear evaluation metrics for accuracy, latency, and cost
• Develop scalable backend services for document processing (PDF/OCR/CSV), async job queues, case lifecycle orchestration, and risk scoring with confidence-driven UX and human-in-the-loop controls
• Own the productionization of AI systems, including evaluation pipelines, dataset/version management, and safe rollout strategies (A/B testing, guardrails, fallback behavior)
• Harden the platform for enterprise: auth controls, role-based access, audit trails, backups, and monitoring with measurable SLOs
• Establish CI/CD, deployment pipelines, runbooks, and incident response practices from the ground up
• Propose and engage in cutting-edge AI research related to our mission, particularly around agentic reasoning over regulatory and financial data
• Work directly with the founding team to define architecture, technical roadmap, and product direction

Skills

TypeScript

Python

LLM integrations

Document processing

API design

Async job processing

Ownership mindset

Startup experience

Frontend/backend stacks

Tools

LangChain

LlamaIndex

Job description

Manhattan Labs, in San Francisco, is seeking a founding engineer to architect and build an AI-native platform for regulatory compliance. You’ll shape the system, own critical technical decisions, and partner with the founding team to push our enterprise-ready vision from MVP to production.

You’ll design agentic reasoning, large-scale document ingestion, and user-facing tools while ensuring regulatory scrutiny and reliability for financial institutions.