Hybrid Technical Support Specialist — Data & AI Fixes

Alloy.ai

Washington

Hybrid

USD 65,000 - 80,000

Full time

9 days ago

Application generator

A complete application in a minute — tailored resume and cover letter, ready to send.

Get past ATS filters

Job summary

Alloy.ai is seeking a Customer Support Specialist to diagnose complex data issues and deliver durable fixes, becoming a front-line contact for customers. You will own content creation, onboarding, and training resources, while helping improve Lens and the AI knowledge base.

This hybrid role emphasizes proactive problem solving, cross‑functional collaboration, and scalable support evolution in a fast-growing startup.

Qualifications

Bachelor’s or associate’s degree in a technical or related field or equivalent SaaS work experience.
Two or more years in a technical support, solutions or data role.
Demonstrated experience investigating and resolving complex data issues, and fixing causes not symptoms.
Hands‑on experience using AI tools to accelerate technical investigation.
Experience communicating technical knowledge to both technical and non‑technical audiences.
Experience creating documentation or training content (help articles, runbooks, onboarding guides).
Comfort delivering training and onboarding directly to users.
Knowledge of customer service best practices and experience supporting software issues.
Experience with AI knowledge bases or prompt/context engineering is a strong plus.
Industry experience in consumer goods, retail or supply chain is a plus.
Effective time management and ability to handle multiple inquiries.

Responsibilities

Triage inbound tickets and resolve the majority of them.
Respond to customer queries in a timely and accurate way via Alloy’s ticketing system.
Investigate complex data issues end to end—tracing discrepancies through raw retailer files, extractor logic, master data and ingestion behavior to establish the root cause before applying a fix.
Identify recurring issues and drive them to permanent resolution—proposing extractor changes, guardrails, monitoring or product fixes.
Use AI tools to investigate faster—summarizing large files, comparing datasets, drafting queries and narrowing hypotheses.
Improve the knowledge base our AI support draws on: writing and maintaining help articles, closing gaps you see in Lens’s answers.
Document the things customers keep needing: how people actually use Alloy to solve a given problem, best practices, and retailer context.
Think about the architecture of our knowledge: what belongs in help articles vs internal docs vs Lens’s context.
Build and run enablement for our customers—onboarding material, training and self-serve content.
Proactively seek opportunities to improve internal processes & the wider customer experience.
Collaborate cross-functionally to maintain high levels of product knowledge and share actionable customer insights.