
Support Engineer, AI & Operations
What you need
- Experience in technical support, software development, or technical operations
- Programming knowledge to read code and make small fixes with AI
- Practical experience using AI tools for debugging and coding, verifying output
- Comfort with SQL, CSV, logs, APIs, command-line tools
- Familiarity with Git, pull requests, testing before release
What you'll do
- Investigate and resolve support requests, reproduce issues, distinguish bugs
- Provide clear answers, verify against code/docs, keep users updated
- Make small AI-assisted fixes, write tests, prepare pull requests
- Run recurring technical operations, investigate failures, improve procedures
- Maintain automations, prototype improvements, write docs, escalate with context
Location: United States — fully remote. Candidates must reside in the United States.
Compensation: $60,000–$80,000 annual base salary, depending on relevant experience and skills.
Benefits: Health insurance, 401(k), equity, flexible remote work (quarterly onsite)
US visas: U.S. work authorization required (no H-1B / no visa sponsorship)
About Malama Health (YC S22)
Malama Health builds technology that helps members, care teams, and health plan partners improve access to care and health outcomes. We’re a small team where solving a confusing workflow or fixing a recurring bug can make a meaningful difference in someone’s day.
The Role
We’re looking for a Support Engineer who enjoys figuring out why something isn’t working, explaining it clearly, and following through until it’s resolved. You’ll work closely with our care, operations, and engineering teams to answer product questions, troubleshoot issues, make focused bug fixes, and keep day-to-day technical operations running reliably.
AI will be part of your everyday workflow: helping you navigate the codebase, investigate issues, write small fixes and scripts, and draft clear explanations. You’ll bring the judgment to check its work, test changes, and know when to ask for help.
Your primary focus will be supporting and improving our existing systems. You won’t be expected to independently design and build complete product features or own major architecture decisions. You should be comfortable reading code, making scoped changes with AI assistance, and taking responsibility for the result.
What You’ll Do
- Investigate and resolve support requests. Work with care managers and operations teammates to reproduce issues, clarify expected behavior, and distinguish bugs from data, configuration, or workflow problems.
- Give clear, useful answers. Explain how the product works in plain language, share practical next steps, and keep people updated until their issue is resolved. Verify answers against the application, documentation, code, or relevant data.
- Make small, reliable fixes using AI. Use AI coding tools to trace problems, propose focused changes, add or run relevant tests, and prepare pull requests for engineering review.
- Run recurring technical operations. Follow and improve documented procedures for data imports and exports, file transfers, scheduled jobs, integrations, and approved account setup or maintenance tasks. Check that each workflow actually completed and investigate failures.
- Maintain lightweight automations. Troubleshoot scripts and browser-based workflows, reduce repetitive manual work, and make recurring tasks easier for the team to run.
- Prototype practical improvements. Work with teammates to understand a workflow problem, use AI and existing tools to put together a small working prototype, and refine it based on feedback. Bring promising ideas to engineering for review before production use.
- Turn repeated questions into better documentation. Write troubleshooting guides, FAQs, and runbooks so teammates can solve common issues more independently.
- Escalate with context. Bring engineering a clear problem statement, reproduction steps, impact, and what you’ve already checked when an issue needs deeper expertise. Follow through on the handoff.
- Handle sensitive data carefully. Use approved tools and access, protect member information, and follow review and approval procedures for production changes.
What We’re Looking For
- Experience in technical support, application support, software development, QA, technical operations, or similar hands-on work.
- Enough programming knowledge to read existing code, understand a proposed change, and make small fixes or scripts with AI assistance.
- Practical experience using AI tools for debugging, coding, or investigation, with a habit of checking their output.
- A hacker’s mindset: you’re curious, resourceful, and willing to experiment with unfamiliar tools. You enjoy figuring out how to make something useful work, whether that’s a script, an automation, or a simple prototype.
- Practical product sense: you ask what the user is trying to accomplish, spot unnecessary friction, and choose a simple solution that meets the need. You’re comfortable clarifying an ambiguous request and testing an idea with the people who will use it.
- Comfort with SQL, spreadsheets or CSV files, logs, APIs, and basic command-line tools.
- Familiarity with Git, pull requests, and testing changes before release.
- Clear written communication and patience when helping people with different levels of technical knowledge.
- Strong follow-through: you organize requests, prioritize by impact, document what happened, and confirm that the problem is resolved.
- Good judgment about uncertainty, access, and when an issue needs engineering or operations input.
Nice to Have
- Familiarity with Ruby on Rails, JavaScript or React, React Native, or AWS. Our existing engineering stack includes Rails, React Native, and AWS; you do not need to be an expert in every part of it.
- Experience supporting healthcare software, care teams, or other environments that handle sensitive information.
- Experience with SFTP, scheduled jobs, third-party integrations, or browser automation.
- Experience at a small company where support, engineering, and operations work closely together.
What Success Looks Like
- Care and operations teammates receive accurate answers and know what happens next.
- Routine issues are resolved with minimal engineering involvement, while complex issues reach the right person with useful context.
- Bug fixes are small, reviewed, tested, and checked after release.
- Recurring workflows complete reliably, and failures are caught and addressed.
- Repeated support requests lead to clearer documentation or practical improvements.
Why Malama Health
- Work that directly supports care delivery and helps people get the services they need.
- Hands-on experience using AI to solve real software and operational problems.
- Close collaboration with engineering, clinical, and operations teammates.
- Ownership of practical improvements you can see making a difference.
How to Apply
Apply through YC with your resume and a short example of a technical problem you investigated or solved. If you used AI, tell us how you checked the answer or fix.
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About Malama Health
Doula-led holistic support during and after pregnancy
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