Director of AI Engineering

Role Description

Ottimate is building the AI-native future of accounts payable. Our platform processes millions of invoices across hundreds of enterprise customers, powered by a suite of ML models and agentic workflows. As Director of AI Engineering, you will own the full AI and ML layer of our product — from invoice understanding and vendor intelligence to our conversational AP Copilot and the next generation of autonomous AP agents.

This is a hands-on leadership role. You will spend at least half your time writing code, architecting systems, and driving technical decisions alongside your team. You will also set the AI roadmap, partner cross-functionally with Product, Data, and Platform Engineering, and manage a distributed team of 8–10 engineers across Data and ML.

We are looking for a senior technical manager or director — ideally someone who has thrived at a smaller company and is ready for a career step up into broader ownership. If you are energized by shipping real AI products, working with noisy real-world financial data, and building the systems that will define how enterprises automate AP, this role is for you.

Responsibilities

• Technical Leadership
  • Architect and ship production AI/ML systems — you write code, not just review it
  • Own the AI roadmap end-to-end: prioritization, trade-offs, delivery
  • Set technical standards for model quality, evals, observability, and reliability
  • Drive adoption of agentic coding tools to multiply team velocity
  • Claude Code, Cursor, Copilot, or equivalent — measure and improve PR throughput
  • Partner with Platform Engineering on infrastructure, data pipelines, and APIs
• People & Cross-Functional
  • Manage a distributed team of 8–10 engineers across Data and ML disciplines
  • Hire, develop, and retain engineers at all levels; build a high-trust remote culture
  • Partner with Product on roadmap sequencing and scope trade-offs
  • Work directly with customer-facing teams to close feedback loops on model quality
  • Communicate AI capabilities and limitations clearly to non-technical stakeholders
• Model & Systems Ownership
  • Own model performance metrics and drive continuous improvement pipelines
  • Build and maintain evals frameworks — regression suites, human review, A/B testing
  • Oversee training data collection, curation, and labeling operations
  • Manage the full ML lifecycle: experimentation, deployment, monitoring, iteration
  • Define and enforce quality bars for agentic workflows entering production
• Applied AI & Agentic Systems
  • Production agentic pipelines using frontier models
  • Anthropic SDK · OpenAI SDK · tool use, function calling, multi-agent orchestration
  • Reliable agent loop design — planning, memory, tool execution, error recovery
  • RAG pipeline design — chunking, embedding models, retrieval tuning, reranking
  • Evals frameworks built from scratch — correctness, regression, semantic similarity
  • Observability for production AI — tracing, cost tracking, latency, failure analysis
• Model Expertise
  • Fine-tuning frontier or open-source models for domain-specific tasks
  • LoRA, QLoRA, instruction tuning — not just off-the-shelf API calls
  • Training data collection, curation, cleaning, and labeling at scale
  • LLM inference and serving optimization
  • vLLM, TGI, or equivalent
  • Model selection trade-offs — cost, latency, capability, context window
• Engineering Depth
  • Hands-on Python — comfortable writing, reviewing, and shipping production code
  • PostgreSQL — schema design, query optimization, indexing strategies
  • Distributed systems — async workers, queues, retries, state machines
  • Celery or similar async task frameworks is a bonus
  • Public-facing API design — REST, versioning, developer experience
  • MCP server development — tool-accessible APIs for AI agent integration
  • AWS or cloud infrastructure — enough to own AI workload deployments

Qualifications

• Engineering Manager ready for director-level ownership
• Has led technical teams at a startup or growth-stage company — knows how to move fast
• Hands-on contributor who has also managed small high performance teams
• Comfortable owning outcomes

Industry Experience

• Finance and/or AP domain — invoice workflows, GL coding, vendor management
• Hospitality — high-volume, multi-location AP operations
• Noisy, unstructured text data — OCR outputs, inconsistent supplier formats, entity resolution at scale

Benefits

• Compensation: 200,000-225,000 + 15% Annual Bonus + Equity
• Competitive salary based on skills & experience
• Medical, Dental, Vision and other Company-Subsidized Benefits for you and your family
• Employer sponsored 401(k) with company match
• Paid Time Off (and the encouragement to use it)
• Annual company retreats
• Promote from within philosophy