User Support Lead

Figure AI
San Jose, CA
On-siteCareer-pivot friendly

Who this role is best for

Best suited to candidates with leadership experience in technical support environments working in software product companies.

Best fit for

  • Candidates with leadership experience in technical support environments and a track record of scaling support operations
    — “track record of building a support operation from scratch or scaling one significantly
  • Individuals with hands-on experience in modern support platforms and AI agent flows
    — “Hands-on experience administering and optimizing modern support platforms such as Sierra, Intercom, or similar tools
  • Candidates who have experience translating user reports into actionable bug tickets for engineering teams
    — “Design workflows that turn user reports into well-documented, reproducible, prioritized bug tickets for engineering

Things to consider

  • The role demands a high level of technical troubleshooting and bug reproduction skills
    — “Strong technical troubleshooting instincts: able to reproduce issues, isolate variables, and write bug reports engineers can act on immediately
  • Candidates must be comfortable with data-driven decision-making and reporting to leadership
    — “Strong analytical skills; comfortable using support data to drive decisions and report to leadership

How to stand out

  • Highlight your experience in building support teams and scaling operations in your resume and interviews
    — “Build and operate the support queue, ensuring inbound issues are answered, investigated, and resolved within response-time and satisfaction targets
  • Showcase your ability to design and implement AI agent flows and macros within support platforms
    — “Build, configure, and continuously improve our support stack using platforms such as Sierra and Intercom, including AI agent flows, macros, and escalation paths
  • Emphasize your track record in creating internal documentation and triage playbooks
    — “Create and maintain internal documentation, triage playbooks, and a self-serve knowledge base to deflect repeat issues
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build and scale user support team
  • improve product quality through support
Typical background
5+ years in user supportteam leadership

Skills & requirements

Required

User SupportTeam ManagementProcess DesignToolingQuality Assurance

Preferred

AI Agent FlowsJira

Stack & domain

User SupportCustomer SupportSupport PlatformsAi-powered Support AgentsBug TriageCommunicationLeadershipProblem-solvingSoftware Product SupportInternal Application Support

About the role

Original posting from Figure AI via Greenhouse

We are looking for a User Support Lead to build, run, and scale our user support team. Your team will be the first line of response for our users. Its core mission is to surface, reproduce, and route bugs in our internal application quickly and accurately so that engineering can fix what matters most. You will own the support operation end to end: the people, the processes, and the tooling. This is a high-ownership role where great support work directly improves the quality of the product.

Responsibilities

Own the full user support function: strategy, day-to-day operations, tooling, and quality

Build and operate the support queue, ensuring inbound issues are answered, investigated, and resolved within response-time and satisfaction targets

Build the team: hire, onboard, coach, and manage support specialists as volume and scope grow

Design workflows that turn user reports into well-documented, reproducible, prioritized bug tickets for engineering

Build, configure, and continuously improve our support stack using platforms such as Sierra and Intercom, including AI agent flows, macros, and escalation paths

Create and maintain internal documentation, triage playbooks, and a self-serve knowledge base to deflect repeat issues

Define and report on key metrics for both support performance (CSAT, first response time, resolution time) and bug discovery (time to reproduction, escalation accuracy, defect signal quality)

Serve as the escalation point for complex, sensitive, or high-priority issues

Partner closely with engineering and product to triage findings, identify recurring pain points, and close the loop with affected users

Requirements

5+ years of experience in user or customer support for a software product, including 2+ years building or leading a support team

Hands-on experience administering and optimizing modern support platforms such as Sierra, Intercom, or similar tools (e.g., Zendesk, Front, Ada)

Experience deploying and tuning AI-powered support agents, including flow design, guardrails, and escalation logic

Strong technical troubleshooting instincts: able to reproduce issues, isolate variables, and write bug reports engineers can act on immediately

Track record of building a support operation from scratch or scaling one significantly

Excellent written communication: clear, warm, and precise with users and internal teams alike

Strong analytical skills; comfortable using support data to drive decisions and report to leadership

Bonus Qualifications

Experience running support for internal tools or technical user bases

Familiarity with JIRA (or similar) for bug triage and cross-team escalation

Experience with QA or defect management processes

Experience defining SLAs and building QA programs for support quality

A passion for helping scale the deployment of humanoid robots

Compensation & Benefits

The US base salary range for this full-time position is between $120,000 - $175,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended. Leveling and title may be adjusted based on candidate experience and feedback throughout the interview process.

Source: Figure AI careers (Greenhouse)

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