AI Engineer
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Job Description
AI Engineer building Agent OS runtime, tools, memory, trust, and evaluation infrastructure. Powering safe AI agents for ServiceTitan’s contractor-management platform.
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
- Contribute to tradeoffs involving latency, cost, quality, structured outputs, caching, fallback behavior, provider choice and model routing
- Write production code and build reliable APIs, workflows and services for agent execution
- Review teammates' implementations
- 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 and define platform contracts
Requirements:
- B.S., M.S. or PhD (or equivalent practical experience) in Computer Science, Engineering, Physics or a related field
- 0-3 years of professional, internship or substantial project experience building software
- Strong hands-on coding ability in Python or a comparable backend language such as TypeScript, C# or Java
- Clean, tested code
- Practical understanding of LLM application basics: prompt and context assembly, retrieval, tool calling, structured outputs and agent workflows
- Working knowledge of SQL and databases, REST APIs, Git and async or background processing
- Production-safety instincts involving failure modes, validation, permissions, idempotency, audit trails and monitoring
- Good engineering judgment and clear written and verbal communication
- Experience with AI, ML, data, platform, infrastructure, workflow, automation or developer-platform systems in production preferred
- Experience with modern LLM architecture preferred
- Exposure to distributed or event-driven systems preferred
- Experience designing or operating evaluation systems preferred
- Knowledge of unstructured data, vector search, metadata, provenance, freshness, source authority and privacy boundaries preferred
- Experience with PostgreSQL, SQL Server, Snowflake, BigQuery, Elasticsearch or vector stores preferred
- Experience building services on Azure, AWS or GCP preferred
- Awareness of reliability, security, observability and multi-tenant SaaS constraints preferred
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 insurance
- 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 $20k in fertility services (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
- Equity
- Holistic suite of benefits
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