Technical Support Engineer West Coast
Job Location:
San Francisco, CA - USA
Monthly Salary:
Posted on:
Vacancies:
Job Summary
About Monte Carlo
Monte Carlo is the agent trust platform that unifies data and agent observability to monitor troubleshoot and improve production AI systems. As enterprises prepare to deploy thousands of agents across business-critical use cases Monte Carlo provides the reliability infrastructure to support them along this AI transformation from human-guided agents to fully autonomous operations. Founded in 2019 and backed by leading investors Monte Carlo empowers data and AI teams to ship trusted AI at scale. Learn more at .
The Role
Monte Carlo is hiring Technical Support Engineers to own the end-to-end customer experience when things go wrong from the first Slack message to closing the loop with Engineering. This is not a ticket-routing function. Youll dig into customer data stacks reproduce issues in complex environments write internal runbooks and ship fixes to production as a regular part of the job not an exception.
Youll be joining at a moment when the support function is being rebuilt with AI tooling and proper engineering rigor which means youll have real input into how this team operates.
Location: US West Coast (Pacific time zone). This role works closely with West Coast customers and partners PT hours are required.
What Youll Do
Diagnose and resolve technical issues across Monte Carlos platform data pipelines monitors alerts integrations and agent observability features using logs SQL APIs and whatever it takes
Own issues end-to-end: triage reproduce escalate to Engineering when needed validate fixes and close the loop with customers
Build and maintain documentation runbooks and a knowledge base that actually reduces ticket volume over time
Work alongside the team building AI-powered support tooling contribute to prompt design test coverage and escalation logic for the bot handling tier-1 setup and FAQ
Partner with Engineering and Product on bugs and feature gaps youre the person who can say Ive seen this five times this week with receipts
Drive high-priority customer issues over the line own the coordination across Engineering CS and the customer keep everyone aligned and dont let urgency get lost in someone elses backlog.
Collaborate with Customer Success Sales and Field Engineering to ensure customer issues dont fall into gaps between teams
Use AI to surface patterns across cases and bring them to Engineering and Product with data then build or contribute to the automation that handles those patterns so the team can focus on the complex ones
What Were Looking For
Technical Depth 2 years in a technical support solutions engineering or SRE-adjacent role. Comfortable reading logs writing SQL using Postman and navigating cloud environments (AWS GCP Azure).
Codebase Fluency Comfortable finding your way around a Python repo: reading PRs writing fixes running tests. You dont need to be a full-stack engineer but you should be able to ship a patch.
Data Stack Fluency You know the modern data stack well enough to hold your own: Snowflake Databricks BigQuery dbt Airflow or similar. Customers run complex pipelines and youll need to understand whats happening.
AI-Fluent You understand how AI agents and ML-driven systems can fail. Youre not intimidated by probabilistic outputs model drift or it worked yesterday. Youve used AI coding assistants and LLM tools actively in your workflow to write runbooks debug faster draft responses or prototype automations not just experimented once. Bonus: youve contributed to or tested AI-powered support tooling.
Customer Communication Clear calm and honest under pressure. You can explain something technically complex to a data engineer and to a VP of Data in the same ticket.
Builder Mentality You write docs without being asked. You notice when a process is broken and propose a fix. Youd rather use AI to automate a repetitive support task than do it manually three more times and you have examples of doing exactly that.
This Is Not For You If
You need a well-defined playbook before you can start were still writing it
You see documentation as overhead rather than part of the job
You prefer structure and clear escalation paths over owning issues end-to-end
You want a role where the interesting technical challenges live elsewhere
Why Monte Carlo
End-to-end ownership youll actually close issues not just route them
AI support tooling youll contribute to building an AI-assisted support function not just use someone elses bot
Roadmap influence your case patterns directly feed product and engineering priorities
#LI-REMOTE
#BI-REMOTE
Come As You Are
Equality is a core tenet of Monte Carlos culture. We are committed to building an inclusive global team that represents a variety of backgrounds perspectives beliefs and experiences.
Monte Carlo is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
We are proud to be recognized for our world-class employee experience:
Monte Carlo Named 2025 Databricks Data Governance Partner of the Year
Monte Carlo Named to G2s Best Software Products of 2026
We are super proud to be named the 2026 Best Place to Work by Built In!
Beware of Imposter Recruiters and Job Scams
All official communication from our recruiting team will come from an @ email address.
We will never ask candidates to provide sensitive personal information (such as bank details social security numbers or payment) at any stage of the recruitment process.
We will never request payment for equipment training or application processing.
Our open positions are always listed on our official careers page: you are contacted by someone claiming to represent Monte Carlo but youre unsure of their legitimacy please reach out to us directly at before sharing any personal information.
Required Experience:
IC
About Company
Monte Carlo’s Data Observability platform increases trust in data by eliminating data downtime, so engineers innovate more and fix less.
