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Technical Support Engineer

AI Summary
Clipboard is seeking a Technical Support Engineer to serve as the escalation point between customer support, engineering, and product teams. The role investigates and reproduces complex platform, data, API, and configuration issues using SQL, Datadog, logs, and internal tools. The engineer manages live incidents, communicates structured updates, implements appropriate fixes, and creates evidence-backed escalations for engineering review. Success requires rigorous root-cause analysis, clear documentation, proactive prevention thinking, and comfort working rotating five-day schedules that include weekends. This is a remote APAC position supporting a large healthcare staffing marketplace operating around the clock.
Remote from
APAC
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
10 Dec 2026
Listing views
27
Application actions
3
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Opportunity details

About this role.

About Clipboard

Our mission is to uplift as many communities as possible. We do this through our app-based marketplace that connects healthcare professionals with the workplaces that need amazing workers. This enables hundreds of thousands of people to achieve financial stability for themselves and their families while providing essential care to millions of people across the U.S.

Founded in 2016, we are a remote-first team of over 1,000 people building a top Y-Combinator company and have been profitable since 2022. We’re the leader in Long-Term Care staffing and are rapidly expanding into Home Health, Hospitals, and more, meaning we have more work to do than people to do it, and are growing our team to support millions more people and their communities.

Overview

📍 Remote – APAC

Want to sit at the intersection of Support, Engineering, and Product? Clipboard is hiring Technical Support Engineers (TSEs) to act as the primary escalation layer for technical issues across our platform. You’ll own the investigation, reproduction, and – where applicable- agent-assisted fix implementation that turns noisy customer reports into validated, high-signal work, so Engineering only receives production-ready problems for final review.

This is a hands-on, high-ownership role for people who love digging into hard problems with real diagnostic tools, who care about getting to the root cause rather than just clearing a queue, and who want their investigations to directly protect platform reliability for hundreds of thousands of healthcare workers and the facilities that depend on them.

What You’ll Do

  • Monitor escalation channels and the Technical Support queue in Zendesk, catching early signals of systemic problems before they reach customers

  • Investigate complex product, platform, and data-layer issues using tools like Datadog, internal dashboards, and SQL, reproducing bugs and producing evidence-backed escalations to Engineering.

  • Handle live incidents end-to-end, from detection to closure: React to an incident with urgency, coordinate across Support, Engineering, and Product, and keep stakeholders updated with clear, structured communication

  • Implement fixes where appropriate, testing your changes before handing off to Engineering for final review and sign-off

  • Perform Root Cause Analysis and post-incident reviews, translating each issue into learnings that reduce recurrence and improve monitoring

  • Maintain operational workflows (geofence, facility quizzes, NFC) accurately and quickly while spotting trends for prevention

  • Capture investigative learnings in clear troubleshooting guides and documentation, and submit structured proposals that turn recurring patterns into actionable improvements

  • Uphold our values such as unreasonably fast, ownership, and uncomfortably high standards in every interaction

Who We’re Looking For

  • Technical Fluency – You’re comfortable investigating issues with observability tools (e.g., Datadog), writing SQL to interrogate data, and reasoning about APIs, backend configurations, and feature toggles. You can tell the difference between a UI, data, and code-level problem.

  • Diagnostic Rigor – Every investigation you produce is thorough, evidence-based, and reproducible. You rule out config and data causes before escalating, and your write-ups are clear enough for another engineer to pick up without rework.

  • End-to-End Ownership – You own problems from first report to confirmed resolution, including stakeholder updates and follow-through, with no gaps between hand-offs.

  • Composure Under Pressure – You stay structured and calm during live incidents, balancing speed with accuracy and communicating clearly when stakes are high.

  • Adaptability & Prioritization – You juggle structured work (incidents, bugs, workflows) with unplanned high-priority requests without letting SLAs slip.

  • Systems & Prevention Thinking – You treat every issue as a chance to learn, identifying gaps in monitoring, tooling, or process and proposing fixes that prevent recurrence.

  • Fluent, professional-level English communication, both written and verbal.

Nice to Have

  • Experience with observability and analytics tooling (Datadog, Sentry, Snowflake, or similar)

  • Familiarity with SQL and reading application logs

  • Background in technical support, SRE, incident response, or a related engineering-adjacent function

  • Exposure to AI-assisted coding/agent tooling

  • Experience in Ops, Support, or CX environments at scale

Hiring Process

  • Application Review

  • Skills Assessment via Case Study

  • Case Interview with Tech Support Team Lead

  • Interview with Head of Worker Experience

Important Note: Clipboard operates 24/7. Team members work 5 days within a 7-day schedule, including weekend availability. Shifts are assigned based on business needs.

Quick Note on Scammers:

Clipboard would never ask you for money or your bank details to participate in our hiring process. Report any scammers impersonating the Clipboard hiring team members here.

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe role combines production incident handling with technical investigation across data, backend configuration, observability tooling, and support workflows. It requires fast independent judgment while maintaining high-quality evidence and stakeholder communication during live issues.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$75,000
US market range (per year)$60k–$95k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation was disclosed. The yearly cadence and USD market estimate are inferred for a full-time Technical Support Engineer role; estimated annual market range is $60,000–$95,000 USD, with a midpoint of $75,000 USD.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you investigate a report that users cannot complete a critical workflow, but the application appears healthy at a high level?

I would first clarify the affected user segment, timestamps, workflow step, and expected versus actual behavior. Then I would review dashboards and logs, query relevant records with SQL, check feature flags and configuration, and attempt to reproduce the issue. I would document evidence, assess customer impact, communicate status, and escalate a concise reproducible case if engineering intervention is needed.

Describe how you would distinguish between a UI defect, a data issue, and a backend issue.

I would compare the UI behavior with API responses, logs, and underlying database records. A UI issue may show correct API and data results but render or validate them incorrectly; a data issue appears when records are missing, stale, or malformed; a backend issue is indicated by failed API requests, incorrect service logic, or server errors. I would validate each layer before deciding on the escalation path.

What should be included in a high-quality engineering escalation?

It should include impact and severity, affected users or facilities, exact timestamps, reproduction steps, expected and actual results, relevant identifiers, screenshots or log references, SQL findings where appropriate, and troubleshooting already completed. The goal is to make the problem actionable without requiring the receiving engineer to repeat the investigation.

How would you manage a live production incident involving Support, Product, and Engineering?

I would establish the incident scope and owner, gather initial evidence, and set a predictable communication cadence. I would prioritize mitigation and customer impact reduction while keeping updates factual, concise, and separated from unverified hypotheses. After resolution, I would verify recovery, document the timeline, lead or contribute to root-cause analysis, and propose preventive monitoring or process improvements.

How do you balance a busy technical-support queue with an unexpected urgent incident?

I would immediately assess severity, scope, and SLA risk, then prioritize the incident if it affects a critical workflow or many users. I would communicate the prioritization decision, delegate or pause lower-risk work where possible, and keep the queue visible through clear status updates. Once the incident is stable, I would return to queued work using impact, urgency, and recurrence risk to order tasks.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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