Director of AI Engineering

About this role

Location : Remote - United States only. About the role: 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 Requirements 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 Ideal Career Background 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 ★ Industry experience above is a bonus Exceptional AI engineering skills are the primary bar. We will teach the domain. Benefits We care deeply about making Ottimate an incredible place to work and invest a significant amount of time and energy into creating and maintaining a company culture that provides our team with a generous level of support whilst inspiring them to do their best work. The specific benefits/perks we offer are continually evolving, but currently include: 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. Beyond the tangible benefits though: You will be part of a growing team, at a pinnacle moment of scale for the business, and experience the excitement of working in a startup where each action makes a huge difference. You will have the agency to solve difficult problems creatively, the freedom to explore work that inspires you, and infrastructure to ensure you're constantly challenged and developing. You will work with sharp, passionate teammates solving some of the most unique challenges and positioning our product as a premier finance automation solution. Our commitment to empowering a diverse and inclusive workforce, celebrating differences, and creating a safe space for our employees to bring their whole selves to work is second to note. We are transforming entire industries using innovative technology inc