Senior Manager, AI Engineering (Agent OS Platform)

ServiceTitan•US CA Remote, CA

1d•$223,600 - $358,900•Remote

About The Position

ServiceTitan is building Agent OS, a shared platform that powers role-specific AI experiences across Atlas, field, office, voice, mobile, and future product surfaces. Agent OS provides the runtime, context, memory, action, trust, and evaluation layers needed for AI agents to help contractors run their businesses safely, observably, and at enterprise scale. The Senior Manager, AI Engineering will lead a compact, hands-on AI platform engineering team responsible for foundational Agent OS capabilities. This is a builder-manager role combining team leadership, architecture, technical decision-making, and close involvement in design, implementation, debugging, evaluation, and production delivery. The role is expected to turn strategy into sequenced platform work that ships quickly while avoiding one-off agent implementations. The team’s scope includes agent runtime and workflow execution; context and memory systems; reusable domain capabilities; typed actions, permissions, approvals, and auditability; evaluation and observability; and secure integration with ServiceTitan systems of record and Atlas. The manager will partner with product, design, architecture, security, data platform, Atlas, and domain engineering teams to deliver useful, safe, measurable agent capabilities. The position also includes hiring, coaching, and retaining engineers. Remote candidates in the United States and Canada will be considered. Candidates based in Pacific Time or able to work significant Pacific Time overlap are highly preferred.

Requirements

12+ years of software engineering experience.
4+ years leading engineering teams or major technical initiatives in a product or platform organization.
Strong technical background as a builder, including the ability to read code, review implementation plans, reason through distributed systems, and debug system behavior.
Recent hands-on technical leadership, such as reviewing design documents, reading implementation details, inspecting production traces or logs, or debugging system behavior within the last 6–12 months.
Experience shipping AI, ML, data, platform, infrastructure, workflow, automation, or developer-platform systems in production.
Practical understanding of modern LLM application architecture, including model gateways, prompt and context assembly, retrieval, tool calling, structured outputs, memory, agent workflows, and human approval patterns.
Understanding of production agent safety, including typed tools, scoped permissions, business invariants, precondition checks, approval thresholds, reversible actions, idempotency, audit trails, and rollback.
Production-minded approach to evaluation, including scenario design, behavioral evaluations, regression suites, trace review, simulation, offline and online metrics, and monitoring for non-deterministic systems.
Strong engineering judgment across APIs, distributed systems, event-driven systems, data platforms, observability, reliability, security, and multi-tenant SaaS constraints.
Strong data and context instincts covering SQL, unstructured data, vector search, metadata, provenance, source authority, freshness, and privacy boundaries.
Ability to turn ambiguous strategy into sequenced roadmaps, measurable outcomes, and clear ownership.
Clear communication with engineers, product leaders, architects, security partners, and executives.
Low-ego coaching style that raises the technical bar while helping the team move faster.

Nice To Haves

Experience building or operating agent runtimes, workflow engines, evaluation platforms, model gateways, ML platforms, developer platforms, or internal control planes.
Experience with approval-gated automation, compliance-sensitive workflows, audit trails, policy engines, or governed writes to systems of record.
Experience integrating AI systems into complex enterprise products where permissions, tenant boundaries, data freshness, customer trust, and reliability are first-order concerns.
Background in SaaS, vertical software, field service, fintech, ERP, CRM, marketplaces, operations, or other domains where software decisions affect real-world business outcomes.

Responsibilities

Lead the team through architecture, implementation, production launch, and rapid iteration.
Review designs and code, inspect traces, debug production behavior, evaluate prototypes, and help engineers make pragmatic tradeoffs.
Translate Agent OS strategy into concrete platform slices that ship quickly without creating one-off agent implementations.
Define platform contracts for role shells, capabilities, tools, actions, approvals, context, memory, evidence, and evaluation.
Establish distinctions between what an agent can do and what it is authorized to do in a tenant, role, workflow state, and risk context.
Partner with Product, Design, Architecture, Security, Data Platform, Atlas, and domain engineering teams to create useful, safe, measurable agent capabilities.
Make evaluation part of everyday engineering through scenario design, regression suites, trace review, simulation, production monitoring, quality gates, and rollout criteria.
Help the team make model and inference tradeoffs involving latency, cost, quality, structured outputs, caching, fallback behavior, and provider choices.
Ensure live ServiceTitan systems of record remain authoritative while memory, retrieval, transcripts, and agent-generated artifacts are governed as contextual evidence.
Work with the team to diagnose agent failures, including wrong tool calls, stale context, missing permissions, unsafe actions, poor retrieval, bad recommendations, latency spikes, and cost regressions.
Hire, coach, and retain strong engineers who can build quickly, reason deeply, and operate responsibly.

Benefits

Flexible time off.
Learning and development opportunities.
Comprehensive onboarding program.
Leadership training and other programs and events.
Bonusly recognition, peer-nominated awards, and other recognition.
Company-paid medical, dental, and vision insurance, with 100% employer-paid options and 90% dependent coverage.
FSA and HSA.
401(k) match.
Telehealth options, including One Medical memberships.
Parental leave and support.
Up to $20,000 in fertility services, including 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.
Annual bonus and equity.