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Salary: USD 90,000 - 150,000 / annual
Charta Health is building an AI-powered operating system for modern healthcare organizations, streamlining workflows across revenue cycle, clinical operations, and administrative functions. Backed by Bain Capital Ventures, the company is focused on making healthcare infrastructure more efficient and accountable.
You will be the first technical line of defense for customer-facing issues. This is not a customer-facing role—your Technical Success Manager teammates own client relationships, while you own the investigation behind them. When a customer reports something wrong (a chart not processed, a code missing, an integration failing, output mismatches), you figure out what happened, why, and what it takes to fix it.
Your core responsibilities:
- Investigate and diagnose incoming issues from the Technical Success team: bugs, data discrepancies, processing gaps, unexpected model output. Reproduce problems, query data, read logs and pipeline runs, and trace issues to root cause.
- Triage with judgment: classify issues quickly (live incident vs. one-off, deployment/configuration vs. product bug vs. expected behavior vs. feature gap). Route incidents to oncall, bugs to the owning engineering pod, and close out working-as-designed cases with evidence.
- Resolve Tier 1 issues directly: fix configuration, mapping, and data issues; re-run failed jobs; correct customer-specific setup; answer definitively whether Charta caused the issue.
- Propose Tier 2 fixes: for code-level defects, identify where in the codebase the problem lives, write up the root cause, and propose a fix—even drafting changes for engineering review. Engineers should receive actionable tickets, not mysteries.
- Hand off cleanly to the customer team: provide clear, plain-English summaries of what happened, what was affected, what's being done, and realistic timelines so Technical Success Managers can confidently communicate with clients.
- Own the loop internally: track every open issue from intake to resolution, follow up with Engineering, confirm fixes in production, and tell the customer team when it's safe to close with the client.
- Build the knowledge base: turn every investigation into reusable knowledge—runbooks, known-issue write-ups, diagnostic queries, triage guides—so recurring questions take minutes instead of hours and the customer team can self-serve more over time.
- Spot patterns: aggregate issues across accounts to surface recurring defects, fragile integrations, and gaps in monitoring or tooling. Bring data-driven recommendations to Product and Engineering about what to fix at the source.
You will work alongside an owning engineering pod for every account, so you always know where escalations go. You are accountable for the quality of triage decisions and for ensuring nothing reaches an engineer that you could have resolved or scoped yourself.
REQUIREMENTS:
- Technically strong: comfortable reading code (Python and/or TypeScript), writing SQL, working through logs and data pipelines, and using AI coding tools to move quickly through unfamiliar codebases. Can work alongside engineers as a peer.
- Relentless debugger: when something doesn't add up, your instinct is to dig until you find the real cause, not the first plausible one. Rule out the obvious (live incident? recent deploy? reproducible?) before escalating.
- Self-sufficient: this role runs on documentation, tooling, and your own initiative. You figure it out yourself and come back with answers, not questions.
- Excellent ticket writer: your escalations are clear, reproducible, and scoped—what happened, the evidence, suspected cause, blast radius, and proposed fix. Engineers are glad to receive them.
- Bilingual communicator: explain a root cause to an engineer in one message and to a non-technical teammate in the next.
- Prioritize under pressure: hold several open investigations at once, tell urgent from important, and keep everyone informed on status.
- Handle sensitive data responsibly: understand that healthcare data demands care and follow access and privacy practices without shortcuts.
- Prior experience in technical support engineering, support/escalation engineering, solutions engineering, SRE/production support, or software engineering—preferably in B2B SaaS where you worked directly in a production codebase and data.
NICE TO HAVE:
- Experience in healthcare technology, especially EHR/EMR integrations (HL7, FHIR, or vendor APIs), medical coding, or risk adjustment.
- Experience supporting data pipelines, workflow orchestration, or ETL systems.
- Experience debugging LLM- or ML-driven products, including evaluating model output and prompt behavior.
- Experience with cloud infrastructure (AWS), observability tools, and ticketing/issue-tracking workflows.
- Experience building internal tools, scripts, or dashboards that made a support team faster.
