Founding Lead Support Engineer (AI)

Location: Berlin, Germany

Company

hirify.global is an AI-first startup helping large enterprises deploy LLM-powered applications and AI systems quickly, combining product development with consultancy services.

What you will do

• Establish and lead the enterprise support function, including support architecture, SLA frameworks, incident escalation paths, and diagnostic runbooks.
• Support Fortune 500 customers during technical calls, uncover workflow pain points, translate requirements, and manage high-stakes account de-escalations.
• Investigate, reproduce, and resolve complex production incidents across web applications, REST APIs, webhooks, microservices, and databases.
• Use SQL, CloudWatch, Datadog, Splunk, GitHub, and related diagnostic tools to trace issues and identify root causes.
• Configure and deploy AI tools and LLM APIs to analyze logs, automate triage workflows, and build self-service knowledge bases.
• Partner with Product and Engineering to turn recurring customer issues into product specifications, bug fixes, and feature enhancements.

Requirements

• 4+ years of hands-on experience in Technical Support Engineering, Solutions Engineering, QA, or SRE in complex enterprise or B2B SaaS environments.
• Experience building processes, setting technical standards, and mentoring engineering colleagues in a fast-paced startup.
• Strong SQL skills for inspecting relational and cloud databases.
• Experience with deep log analysis using CloudWatch, Datadog, Splunk, Grafana, or Loki.
• Working knowledge of REST APIs, JSON payloads, webhooks, HTTP status codes, browser DevTools, SSO, SAML 2.0, OAuth 2.0, and Okta.
• Exceptional verbal and written English communication skills, including advising enterprise executives during live technical calls.

Culture & Benefits

• Work with complex enterprise environments and AI-powered products.
• Operate in a fast product cycle with significant ownership and direct impact.
• Collaborate closely with customers, Product, and Engineering.
• Help shape how large-scale AI systems are deployed in real-world enterprise settings.