Why this role stands out
As the Founding Lead Support Engineer, you'll shape the future of enterprise AI support in a rapidly growing, well-funded startup and enjoy the flexibility of a hybrid work environment. This foundational role is perfect for a seasoned technical leader who excels at building processes and thrives on solving complex challenges for Fortune 500 clients, offering unparalleled opportunity to influence customer success. Apply now to build and lead a critical function from the ground up!
Quick overview
Job description
About Unframe
Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.
Backed by Bessemer, Craft, and TLV Partners with $100M in Series B funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally.
About the role
We are looking for a Founding Lead Support Engineer to establish and lead our enterprise support function while supporting large global enterprise customers using Unframe's AI-powered solutions.
In this founding role, you will be the bridge between our Fortune 500 customers, Product, and Engineering. You will own the technical post-deployment customer experience, dive deep into system architectures, and build the playbooks, processes, and standards that define customer support at Unframe as we scale.
This role is ideal for an experienced technical leader who thrives in early-stage environments, enjoys deep-dive troubleshooting, and wants to shape both our support operations and our AI-first workflows from the ground up.
What you'll do
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Define and build Unframe’s support architecture, SLA frameworks, incident escalation paths, and diagnostic runbooks for our global enterprise coverage.
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Bring technical authority and a consultative presence to live video calls with enterprise bank executives, sponsors, and engineering leads. Uncover workflow pain points, translate requirements, and manage high-stakes account de-escalations with professional poise.
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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.
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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.
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Partner closely with Product and Engineering leadership to turn recurring customer friction and edge cases into actionable product specs, bug fixes, and feature enhancements.
What we're looking for
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4+ years of hands-on experience in Technical Support Engineering, Solutions Engineering, QA, or SRE within complex enterprise or B2B SaaS environments.
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Demonstrated ability to build processes, set technical standards, and mentor engineering colleagues in a fast-paced startup setting.
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Diagnostic Tech Stack:
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Hands-on proficiency writing complex SQL queries to inspect relational and cloud databases.
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Practical experience conducting deep log analysis in CloudWatch, Datadog, Splunk, Grafana, or Loki.
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Solid understanding of REST APIs, JSON payloads, webhooks, HTTP status codes, and browser DevTools.
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Direct working familiarity with enterprise authentication protocols (SSO, SAML 2.0, OAuth 2.0, Okta).
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Daily practitioner of generative AI and agentic coding tools (Claude Code, Cursor, ChatGPT, Copilot) for log parsing, code navigation, and workflow automation.
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Exceptional verbal and written English communication skills, with proven experience advising enterprise executives on live technical calls.
Why join us?
This role is a great fit for someone who enjoys solving real technical problems while working closely with customers, product, and engineering teams. You’ll be exposed to complex enterprise environments, cutting-edge AI products, and fast product cycles with real ownership and direct impact from day one. It’s an opportunity to grow quickly, learn how large-scale AI systems are deployed in the real world, and help shape the experience of some of the world’s biggest companies using Unframe.
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