AI Engineer
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Job Description
AI Engineer building ServiceTitan’s Agent OS platform for contractor business operations. Developing safe agent runtimes, tools, memory, approvals, evaluations, and observability.
Responsibilities:
- Build the runtime for role-specific agents, including tool use, delegation, pause/resume, durable checkpoints, retries, and failure recovery
- Build deterministic controls around non-deterministic reasoning, including governed reads, proposed writes, precondition checks, business invariants, scoped permissions, idempotency, audit trails, and rollback
- Build tenant-scoped context assembly, retrieval, freshness controls, provenance, transcripts, artifacts, tool results, and replayable evidence
- Build human-in-the-loop gates, approval thresholds, reversibility, tenant policy enforcement, and audit history for sensitive workflows
- Build offline and online evaluations, scenario libraries, simulation, trajectory review, regression detection, cost and latency telemetry, and autonomy promotion gates
- Help product teams package prompts, tools, context requirements, policies, evaluations, rollout controls, ownership, and rollback into governed capabilities
- Make model and inference architecture tradeoffs across latency, cost, quality, structured outputs, caching, fallback behavior, provider choice, and model routing
- Design and implement core Agent OS platform services
- Write production code and review implementation details from other engineers
- Build reliable APIs, workflows, tools, and services for agent execution
- Inspect traces, debug failures, and improve production behavior
- Design evaluation scenarios and regression suites for agent workflows
- Partner with domain teams to turn agent use cases into reusable platform patterns
- Contribute to technical direction while staying grounded in what can ship quickly and safely
- Collaborate with Product, Architecture, Security, Data Platform, Atlas, and domain engineering teams
Requirements:
- Skills and experience to build production-grade AI agent platforms
- Ability to build agent runtimes, typed tools, context and memory systems, trust and approval flows, evaluation infrastructure, and production observability
- Ability to design reliable APIs, workflows, tools, and services for agent execution
- Ability to inspect traces, debug failures, and improve production behavior
- Ability to design evaluation scenarios and regression suites for agent workflows
- Ability to address stale context, wrong tool calls, missing permissions, unsafe actions, poor retrieval, latency spikes, and cost regressions
- Ability to define platform contracts for tools, actions, approvals, context, memory, evidence, and evaluation
- Ability to make tradeoffs across latency, cost, quality, structured outputs, caching, fallback behavior, provider choice, and model routing
- Ability to communicate clearly with engineers, product managers, architects, security partners, and engineering leadership
Benefits:
- Flexible time off
- Learning and development opportunities
- Comprehensive onboarding program
- Leadership training
- Programs and events
- Bonusly rewards
- Peer-nominated awards
- Company-paid medical, dental, and vision
- 100% employer-paid options
- 90% coverage for dependents
- FSA and HSA
- 401k match
- Telehealth options including One Medical memberships
- Parental leave and support
- Up to $20k in fertility services, including IUI and IVF
- Surrogacy reimbursement
- 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
- Equity
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