Production Support Specialist
Company Overview
Avantos AI is shaping the future of client relationship management by reimagining it through the lens of artificial intelligence. We are building the industry’s first AI-native operating system for financial services, transforming how firms onboard clients, deliver advice, and manage critical servicing workflows. Our platform consolidates fragmented data, automates complex processes, and embeds intelligent decision-making throughout every stage of the client lifecycle.
Supported by Bessemer Venture Partners and MIT’s investment arm, our team comprises
execution-focused, design-driven, product-centric founders and leaders from Wharton, MIT, top design programs, and unicorn SaaS companies. We move swiftly, tackle deep industry
challenges, and build technology that empowers users to take charge of their workflows.
About the Role
Avantos is the platform enterprise financial firms run their client operations on: the advisor-facing portal, the data ingestion that feeds it, reporting and notifications, third-party integrations, AI-assisted features, and the automated journeys that carry a client process end to end. When any part of it misbehaves in production, you are the person who finds out first, works out what actually happened, gets it to the team that can fix it, and tells the client the truth about it. You will own production issues from detection through investigation, routing, and client communication, to shepherding the fix through UAT into production.
This is a technical coordination, triage, and client advocacy role. You will not write production code day to day, but you do need technical literacy: reading logs and traces, understanding how the pieces of an application fit together, and holding your own in a conversation with engineers. People arrive at that from several directions — technical support, QA, implementation or solutions work, technical operations, or development. What matters is that you have it, not where you picked it up.
Be clear-eyed about one thing. A good deal of this work is manual. Nothing chases a fix ticket into a cycle for you, and two issue trackers do not reconcile themselves. The role suits someone who is systematically persistent rather than someone waiting to be paged.
What You’ll Do
Detection — monitor every intake channel
Watch the client’s Linear board for new tickets and status changes such as Ready for Dev and Failed UAT.
Watch #support in Slack and the help@avantos.ai queue for auto-created SUP tickets, and confirm the auto-reply actually went out.
Watch Datadog monitors and error-rate alerts so we find production problems before the client reports them.
Triage — acknowledge, classify, prioritize
Acknowledge to the client on the ticket, and on the email thread where one exists.
Read the report and establish what it is actually about. Go back to the client when it is not reproducible as written.
Set the real severity against the written rubric. A client-set priority is an input, not the answer.
Set the Customer field and labels so the Linear automations fire correctly.
Investigation — establish first-line root cause
Reproduce the issue in the relevant environment and record the exact steps on the ticket.
Query Datadog logs, traces, and dashboards for the affected service and time window, and attach the evidence.
Separate platform defects from data, configuration, permissions, and user error — and say which it is. Much of what a client sees is tenant configuration rather than product code, and telling the difference is what makes an escalation useful.
Check whether the issue is already known, already fixed on an unreleased branch, or a duplicate.
Routing — assign to the team that can fix it
Route to the engineering triage queue that owns the affected service or surface, never to a default queue.
Link the support ticket as blocked-by the engineering fix ticket so the dependency is visible.
Chase the fix ticket into a cycle, and keep chasing it. Nothing does this automatically.