Senior Manager, AI Engineering (agent Os Platform)

ServiceTitan ServiceTitan · Enterprise · United States · Remote

Senior Engineering Manager to lead a hands-on AI platform team building the core Agent OS, responsible for agent runtime, context/memory, capability platform, action/trust layer, and evaluation/observability harness. Requires strong technical leadership, production experience with LLM applications, and a focus on safety and evaluation.

What you'd actually do

  1. Lead the team through architecture, implementation, production launch, and fast iteration.
  2. Stay hands-on: review designs and code, inspect traces, debug production behavior, evaluate prototypes, and help engineers make pragmatic tradeoffs.
  3. Translate Agent OS strategy into concrete platform slices that ship quickly without creating one-off agent implementations.
  4. Define platform contracts for role shells, capabilities, tools, actions, approvals, context, memory, evidence, and evaluation.
  5. Build the distinction between what an agent can do and what it is authorized to do in a given tenant, role, workflow state, and risk context.

Skills

Required

  • 8+ years of software engineering experience
  • 4+ years leading engineering teams or major technical initiatives
  • Strong technical background as a builder
  • Recent hands-on technical leadership (reviewed design docs, read implementation details, inspected production traces/logs, or debugged system behavior in 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
  • Strong instincts for production agent safety
  • Production-minded approach to evaluation
  • 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
  • Ability to turn ambiguous strategy into sequenced roadmaps, measurable outcomes, and clear ownership
  • Clear communication with engineers, product lead

Nice to have

  • AI
  • ML
  • data
  • platform
  • infrastructure
  • workflow
  • automation
  • developer-platform systems
  • model gateways
  • prompt/context assembly
  • retrieval
  • tool calling
  • structured outputs
  • memory
  • agent workflows
  • human approval patterns
  • typed tools
  • scoped permissions
  • business invariants
  • precondition checks
  • approval thresholds
  • reversible actions
  • idempotency
  • audit trails
  • rollback
  • scenario design
  • behavioral evals
  • regression suites
  • trace review
  • simulation
  • offline/online metrics
  • monitoring for non-deterministic systems
  • distributed systems
  • event-driven systems
  • data platforms
  • observability
  • reliability
  • security
  • multi-tenant SaaS constraints
  • SQL
  • unstructured data
  • vector search
  • metadata
  • provenance
  • source authority
  • freshness
  • privacy boundaries

What the JD emphasized

  • core Agent OS
  • production delivery
  • production scars
  • production launch
  • production AI
  • production agent safety
  • production-minded approach to evaluation
  • production agent failures

Other signals

  • building core agent platform
  • production AI agents
  • evaluating AI systems