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Unframe is an AI-first startup helping enterprises deploy LLM-powered applications at scale. Backed by Bessemer, Craft, and TLV Partners with $100M in Series B funding, the company works with Fortune 500 customers globally, combining product-company speed with consultancy flexibility.
You will be the Founding Lead Support Engineer, establishing and leading Unframe's enterprise support function. This is a founding role where you'll be the technical bridge between Fortune 500 customers, Product, and Engineering teams. You will own the post-deployment customer experience, dive deep into system architectures, and build the playbooks, processes, and standards that define customer support as the company scales.
Key responsibilities:
- Define and build Unframe's support architecture, SLA frameworks, incident escalation paths, and diagnostic runbooks for global enterprise coverage.
- Bring technical authority and consultative presence to live calls with enterprise executives, sponsors, and engineering leads. Uncover workflow pain points, translate requirements, and manage high-stakes account de-escalations.
- Independently investigate, reproduce, and resolve complex production incidents across web applications, REST APIs, webhooks, microservices, and databases. Query SQL databases, parse CloudWatch/Datadog/Splunk logs, trace JSON payloads, and inspect source code in GitHub to isolate root causes before involving core engineering.
- Act as an "AI Support Orchestrator," configuring, testing, and deploying autonomous AI tools (Claude Code, Cursor, Copilot, LLM APIs) to analyze logs, automate triage workflows, and build self-service knowledge bases.
- Partner closely with Product and Engineering leadership to turn recurring customer friction and edge cases into actionable product specs, bug fixes, and feature enhancements.
This role is ideal for an experienced technical leader who thrives in early-stage environments, enjoys deep-dive troubleshooting, and wants to shape both support operations and AI-first workflows from the ground up.
REQUIREMENTS:
- 4+ years of hands-on experience in Technical Support Engineering, Solutions Engineering, QA, or SRE within complex enterprise or B2B SaaS environments.
- Demonstrated ability to build processes, set technical standards, and mentor engineering colleagues in a fast-paced startup setting.
- Diagnostic Tech Stack: hands-on proficiency writing complex SQL queries to inspect relational and cloud databases; practical experience conducting deep log analysis in CloudWatch, Datadog, Splunk, Grafana, or Loki; solid understanding of REST APIs, JSON payloads, webhooks, HTTP status codes, and browser DevTools; direct working familiarity with enterprise authentication protocols (SSO, SAML 2.0, OAuth 2.0, Okta).
- Daily practitioner of generative AI and agentic coding tools (Claude Code, Cursor, ChatGPT, Copilot) for log parsing, code navigation, and workflow automation.
- Exceptional verbal and written English communication skills, with proven experience advising enterprise executives on live technical calls.
