Set the engineering vision and direct the architecture of ServiceTitan's core AI infrastructure and Multi-Agent Systems encompassing model hosting/training, agent hosting, reinforcement learning, intelligence store and rigorous evaluation that bridges agent specifications to business outcomes.
Partner with Product leaders to co-create vision, set strategic direction, and define the technical roadmap for foundational AI capabilities, ensuring the infrastructure seamlessly scales to support all platform-level agents and future product innovations.
Define enterprise-wide standards, budgets, and governance for LLM capabilities and trade-offs (latency, cost) to drive superior customer experiences at scale.
Oversee highly available data processing architectures, Enterprise-wide Knowledge Graphs, and the foundational Intelligence Store, and feedback loops essential for successful RAG and agentic pipelines.
Architect and drive the adoption of scalable LLMOps and AgentOps frameworks.
Direct the architectural integration of advanced techniques (multi-agent systems, function calling, fine-tuning) to enhance agent capabilities and drive operational excellence across the organization.
Align with Engineering and Product leadership on roadmaps to ensure timely delivery of robust production agents that drive revenue and growth.
Implement governance for ethical, explainable, and compliant AI usage, including data handling and bias considerations.
Hire, mentor, and retain a high-performing AI Engineering organization, including developing and coaching engineering managers.

Requirements

MS/Ph.D. in Computer Science, Artificial Intelligence, Computational Linguistics, or a similar quantitative discipline required.
5+ years of experience in ML or AI engineering leadership roles, specifically managing multiple teams (including managing managers) shipping production software.
Deep system-level architectural knowledge of modern NLP, large language models (LLMs), transformer architectures, RAG pipelines, and agentic workflows (planning, reasoning, tool use, human-in-the-loop workflows).
Deep knowledge of evaluation methodologies for non-deterministic systems, including LLM-as-a-Judge, behavioral analysis (evaluating reasoning traces or chain of thought), and championing best practices in model lifecycle management and monitoring.
Expertise in vector databases, and SQL; experience with handling unstructured text data at scale to build foundational data architectures.
Deep architectural understanding and proven experience designing and overseeing the core components of enterprise AI platforms.
Specific architectural expertise in scalable Model Hosting and Training, managing enterprise-wide Knowledge Graphs, building robust Agent Hosting environments, implementing Reinforcement Learning pipelines, and designing a comprehensive Intelligence Store.
Great communication skills, including the ability to communicate complex AI concepts, limitations, and risks to business stakeholders and articulate product vision to audiences.
Proven ability to act as a bridge between Engineering, Product Management, and executive leadership, anticipating future business needs and translating competitive market offerings into scalable technical insights.
Strong judgment in navigating ambiguity and guiding engineering teams in the fast-paced Generative AI landscape.

Benefits

Flexible time off with ample learning and development opportunities to continue growing your career.
Company-paid medical, dental, and vision (with 100% employer paid options and 90% coverage for dependents).
FSA and HSA.
401k match and telehealth options including memberships to One Medical.
Parental leave and support.
Up to $20k in fertility services (i.e. IUI and IVF), surrogacy, and adoption reimbursement.
On demand maternity support through Maven Maternity.
Free breast milk shipping through Maven Milk.
Pet insurance.
Legal advisory services.
Financial planning tools.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningartificial intelligencenatural language processinglarge language modelstransformer architecturesreinforcement learningvector databasesSQLmodel lifecycle managementdata architecture

Soft Skills

communication skillsleadershipmentoringstrategic directioncollaborationjudgmentnavigating ambiguitycoachingstakeholder engagementoperational excellence

Certifications

MS in Computer SciencePh.D. in Artificial IntelligencePh.D. in Computational Linguistics