AI Engineer

Sorry, this job was removed at 03:52 a.m. (UTC) on Sunday, Nov 01, 2026
Hiring Remotely in US
Remote or Hybrid
138K-221K Annually
Junior
Artificial Intelligence • Cloud • Fintech • Machine Learning • Mobile • Software
The operating system for the trades.
The Role
Build core platform infrastructure for production AI agents, including runtime execution, typed tools, context and memory systems, approval workflows, evaluation, observability, and model routing. Develop reliable APIs and services, debug agent failures, design regression suites, and partner with product and engineering teams to create reusable, secure, multi-tenant agent capabilities.
Summary Generated by Built In
Ready to be a Titan?

ServiceTitan runs the businesses behind the trades: jobs, trucks, technicians, equipment, contracts, payments, warranties, compliance obligations, and customer history. That operational context is our advantage. We are building Agent OS to turn that context into safe, observable, production-grade agent work.

Agent OS is the shared runtime, context, memory, action, trust, and evaluation layer behind role-specific AI experiences across Atlas, office, field, voice, mobile, and future product surfaces. This is not a collection of chatbots. It is the platform that lets agents help contractors run their businesses with the right evidence, permissions, approvals, and audit trails.


You will help build the core engineering primitives behind that platform: agent runtime, typed tools, context and memory assembly, trust and approval flows, evaluation infrastructure, and production observability. You are not building one agent for one product surface. You are building the platform that product teams use to build many agents safely.


You will work on a small, senior AI platform team and partner closely with Product, Architecture, Security, Data Platform, Atlas, and domain engineering teams.


What you'll do

You will own well-scoped pieces of the platform, with design and code review from senior engineers, across these areas:

  • Agent runtime and workflow execution: Build the runtime for role-specific agents: tool use, delegation, pause/resume, durable checkpoints, retries and failure recovery. Agents must resume safely without losing state or duplicating side effects.
  • Typed tools and action contracts: Build deterministic controls around non-deterministic reasoning: governed reads, proposed writes, precondition checks, business invariants, scoped permissions, idempotency, audit trails and rollback.
  • Context and memory systems: Build tenant-scoped context assembly, retrieval, freshness controls, provenance, transcripts, artifacts, tool results and replayable evidence. ServiceTitan systems of record stay authoritative; memory provides context and coordination.
  • Trust and approval infrastructure: Build human-in-the-loop gates, approval thresholds, reversibility, tenant policy enforcement and audit history for financial, contractual, dispatch, warranty and compliance-sensitive workflows.
  • Evaluation and observability: Build offline and online evals, scenario libraries, simulation, trajectory review, regression detection, cost and latency telemetry and autonomy promotion gates.
  • Reusable capability platform: Help product teams package prompts, tools, context requirements, policies, evals, rollout controls, ownership and rollback into governed capabilities for owners, CSRs, dispatchers, technicians, managers and back-office teams.
  • Model and inference architecture: Contribute to practical tradeoffs across latency, cost, quality, structured outputs, caching, fallback behavior, provider choice and model routing behind a shared platform layer.

Day to day, you will also:

  • Write production code, build reliable APIs, workflows and services for agent execution, and review teammates' implementations.
  • Inspect traces, debug failures and improve production behavior, working through real failure modes: stale context, wrong tool calls, missing permissions, unsafe actions, poor retrieval, latency spikes and cost regressions.
  • Design evaluation scenarios and regression suites for agent workflows.
  • Partner with domain teams to turn agent use cases into reusable platform patterns, and help define platform contracts for tools, actions, approvals, context, memory, evidence and evaluation.
What you'll bring

Required

  • 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 (strongly preferred) or a comparable backend language such as TypeScript, C# or Java, with clean, tested code.
  • Practical understanding of LLM application basics: prompt and context assembly, retrieval, tool calling, structured outputs and agent workflows. Substantial academic, internship or personal projects count.
  • Working knowledge of SQL and databases, REST APIs, Git and async or background processing.
  • Production-safety instincts: you think about failure modes, validation, permissions, idempotency, audit trails and monitoring, even if you have applied them mainly in projects.
  • Good engineering judgment and clear written and verbal communication.

Preferred (you don't need all of these)

  • Experience building AI, ML, data, platform, infrastructure, workflow, automation or developer-platform systems in production.
  • Experience with modern LLM architecture: model gateways, memory, human approval patterns.
  • Exposure to distributed or event-driven systems: queues, durable execution, message-driven architectures.
  • Experience designing or operating evaluation systems: behavioral evals, regression suites, scenario tests, trajectory review, simulation, online metrics or production monitoring.
  • Data and context instincts: unstructured data, vector search, metadata, provenance, freshness, source authority and privacy boundaries.
  • Experience with databases, warehouses or search systems such as PostgreSQL, SQL Server, Snowflake, BigQuery, Elasticsearch or vector stores.
  • Experience building services on public cloud infrastructure such as Azure, AWS or GCP.
  • Awareness of reliability, security, observability and multi-tenant SaaS constraints.

Be Human With Us:
Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re solving. We’re in this together. Come be human, with us. 


Use of AI Technology:

We use technology, including automated and AI-assisted tools, to support certain aspects of our recruitment process. These tools are designed to improve efficiency and enhance the candidate experience. AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams.


What We Offer:

When you join our team, you’re not just accepting a job. You’re making a career move. Here’s how we’ll support you in doing some of the most impactful work of your career:

  • Flextime, recognition, and support for autonomous work: Flexible time off with ample learning and development opportunities to continue growing your career. We offer a comprehensive onboarding program, leadership training for Titans at all levels, and other programs and events. Great work is rewarded through Bonusly, peer-nominated awards, and more.
  • Holistic health and wellness benefits: 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.
  • Support for Titans at all stages of life: 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, and more.

At ServiceTitan, we celebrate individuality and uniqueness. We believe that the convergence of fresh perspectives and experiences from all walks of life is what makes our product and culture so great. We strongly encourage people from underrepresented groups to apply. We do not discriminate against employees based on race, color, religion, sex, national origin, gender identity or expression, age, disability, pregnancy (including childbirth, breastfeeding, or related medical condition), genetic information, protected military or veteran status, sexual orientation, or any other characteristic protected by applicable federal, state or local laws.

ServiceTitan is committed to fair and equitable compensation for all of our employees. We thoughtfully consider a wide range of factors when determining individual compensation, which may change over time. We comply with all applicable minimum wage laws. For candidates in the United States, the good faith salary ranges estimate for this role is Zone 1: $147,600 USD - $221,400 USD Applicable for: CA, CT, DC, MD, MA, NJ, NY, VA, and WA Zone 2: $137,900 USD - $206,900 USD Applicable for: All other US locations. International Compensation for candidates residing outside the United States will vary by location and will be discussed during the hiring process. Actual compensation within a range is determined by factors including relevant experience, skill set, qualifications, and performance. In addition to base salary, our total compensation package includes an annual bonus, equity, and a holistic suite of benefits.

Skills Required

  • B.S., M.S., or PhD in Computer Science, Engineering, Physics, or a related field, or equivalent practical experience
  • 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
  • Practical understanding of LLM application fundamentals, including prompt and context assembly, retrieval, tool calling, structured outputs, and agent workflows
  • Working knowledge of SQL and databases, REST APIs, Git, and asynchronous or background processing
  • Production-safety awareness involving failure modes, validation, permissions, idempotency, audit trails, and monitoring
  • Good engineering judgment and clear written and verbal communication
  • Experience building AI, ML, data, platform, infrastructure, workflow, automation, or developer-platform systems in production
  • Experience with modern LLM architecture, including model gateways, memory, and human approval patterns
  • Exposure to distributed or event-driven systems, queues, durable execution, or message-driven architectures
  • Experience designing or operating evaluation systems, regression suites, scenario tests, trajectory review, simulation, online metrics, or production monitoring
  • Experience with unstructured data, vector search, metadata, provenance, freshness, source authority, and privacy boundaries
  • Experience with PostgreSQL, SQL Server, Snowflake, BigQuery, Elasticsearch, or vector stores
  • Experience building services on Azure, AWS, or GCP
  • Awareness of reliability, security, observability, and multi-tenant SaaS constraints

ServiceTitan Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ServiceTitan and has not been reviewed or approved by ServiceTitan.

  • Healthcare Strength — Healthcare coverage is positioned as a major strength, with multiple plan features emphasizing broad medical, dental, and vision support plus telehealth-style access. Additional elements like HSA/FSA options and employer contributions reinforce perceived value beyond base pay.
  • Parental & Family Support — Parental leave and family-forming support appear notably robust, with repeated references to paid leave and meaningful adoption/fertility assistance. The package is described as supportive across different family paths, though specifics can vary by plan and location.
  • Fair & Transparent Compensation — Compensation is portrayed as generally competitive in several functions, particularly in engineering and experienced roles, contributing to an overall sense of being paid fairly. Equity and bonus components are also described as meaningful parts of total rewards for many roles.

ServiceTitan Insights

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The Company
HQ: Glendale, CA
2,760 Employees
Year Founded: 2012

What We Do

ServiceTitan is the world’s leading and fastest-growing software technology platform for the trades, a trillion-dollar global industry. We help small business entrepreneurs run and grow their businesses and aim to democratize the power of technology. The trades industry approaches $800B in North America alone and was significantly underserved by traditional software industry leaders prior to ServiceTitan’s entrance to the market. Today, ServiceTitan powers the businesses of more than 5,000 customers, is backed by the world’s leading venture capitalists, and continues to target triple-digit growth annually. ServiceTitan unlocks for small business, the tools and support that big business has enjoyed for decades; helping everyday entrepreneurs run and grow their businesses so they can build better lives for themselves and their families.

Why Work With Us

Not only do we change the lives of our customers, but we strive to create an environment full of opportunities that will change the lives of our employees. We are committed to giving extraordinary talent, extraordinary opportunity, and we prioritize investing in Titans, through a suite of benefits, learning and growth opportunities, and more.

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