---
title: 'Technical Customer Support Specialist at Alloy.ai'
canonical: 'https://feeny.ai/job/technical-customer-support-specialist-alloy-ai-washington-vekstxe9b5sq'
type: 'job'
last_seen: '2026-09-07'
---

# Technical Customer Support Specialist at Alloy.ai

- **Company:** Alloy.ai
- **Location:** Washington, DC
- **Compensation:** $65k–$80k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-04
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.lever.co/alloy/88d36659-b6ea-4106-a6a7-9b07a48f1a80

## Job description

## About Alloy.ai

Alloy.ai is the Commerce Intelligence System for consumer brands. We unify data from 500+ sources — ERPs, retailers, ecommerce platforms, and distributors — into a single source of truth your team can bet their P&L on. Our proprietary commerce logic and AI Agents translate fragmented data into clear demand signals and prepare execution-ready actions — automatically. Sales and Supply Chain teams at brands like Liquid I.V., Crayola, and Valvoline use Alloy.ai to capture every revenue window, protect margins, and keep products on the shelf. From signal to action. Instantly. Alloy.ai is a fast-growing, well-funded startup with an expanding presence across the world. Our team hails from successful startups, leading tech companies and Fortune 100 enterprises. We believe deeply in fostering individual ownership, iterating to excellence, focusing on what matters, communicating openly & respectfully, and supporting one another. We encourage people of all backgrounds to apply. Alloy.ai is committed to creating an inclusive culture, and we celebrate diversity of all kinds.

## About The Role

As a Customer Support Specialist at Alloy, you will be at the forefront of our customers' experience with our software. You will diagnose the root cause of complex data issues and build the durable fixes that stop them recurring. Your technical curiosity is pivotal to delivering unparalleled service and fostering long-term customer relationships.

This role provides Tier 2 and Tier 3 support to our growing customer base. You will investigate user, data, configuration and pipeline requests, working through raw retailer files, product and location master data, extractor logic and ingestion behavior to establish what actually went wrong before you fix it, alongside our engineering, data operations and account management teams.

You will also own the content that keeps those questions from coming back: help centre articles, onboarding material, and training for new users. We do not have a separate L&D function, so this sits with you. You will be closer than anyone to where the product confuses people, and we expect you to turn that into concrete usability feedback rather than absorbing it ticket by ticket.

This role sits at an inflection point. Our AI assistant, Lens, now answers a growing share of the routine questions that once came to Support, and you will help train and improve the knowledge it draws on. Support is changing quickly and we would rather change with it than defend the old shape of the job. The most valuable person here will be someone who measures their success partly by the tickets that stop arriving, and who wants to help define what support looks like when an AI handles the first layer. If that sounds like a diminished version of support work, this is not the right role. If it sounds like the interesting part, we should talk.

## About You

You thrive in a small team where you can make a big impact. As the first person our customers interact with when they have a question or problem, you are high energy and have a positive attitude.

You are genuinely curious about how things work. When something breaks, "it's working again now" is not enough for you—you want to know why it broke, whether it will break again, and what would prevent future recurrences. You are comfortable sitting with a hard problem rather than reaching for the fastest resolution, and you know the difference between fixing an instance and fixing a cause.

You are a self-starter driven by a desire to succeed and have great outcomes for our customers. You are ambitious about what you could become here. You want scope early, you are willing to be uncomfortable to get it, and you would rather be handed a hard problem than a checklist.

You are already using AI tools in your daily work and have opinions about where they help and where they don't. You are excited by the idea of improving an AI support system rather than competing with one, and you see automating away your own repetitive work as a win.

As a key member of our support team, you want to take initiative, tackle new obstacles and help us figure out what scalable support looks like for our growing customer base.

You are strong at time management and the ability to prioritize. You can handle multiple customer inquiries simultaneously and are able to prioritize what needs to be done when in order to make the biggest impact.

## What You'll Do

​​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 rather than repeating the same manual remediation. Use AI tools to investigate faster—summarizing large files, comparing datasets, drafting queries and narrowing hypotheses—while retaining judgment about what the output is telling you. Improve the knowledge base our AI support draws on: writing and maintaining help articles, closing gaps you see in Lens's answers, and feeding real ticket patterns back into its context so it deflects more over time. Document the things customers keep needing: how people actually use Alloy to solve a given problem, the best practices worth recommending, and the retailer-specific context—what a given retailer reports, how their data behaves, what to expect from their feeds. Start to think about the architecture of our knowledge, not just its volume: what belongs in a help article versus internal documentation versus Lens's context, how it stays current, and how someone actually finds it at the moment they need it. Build and run enablement for our customers—onboarding material, training sessions and self-serve content—and measure whether it changes what arrives in the queue. 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.

## What We Are Looking For

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. We care much more about how you think than how long you have been doing it. If you are early in your career but can show us you learn fast and reason well, apply. Demonstrated experience investigating and resolving complex data issues, and a track record of fixing causes rather than symptoms. Comfort working with structured data: reading and comparing large files, understanding data models, identifiers and how records match across systems. Hands-on experience using AI tools (Claude, ChatGPT, Gemini, Copilot or similar) to accelerate technical investigation, with a clear sense of where they are reliable and where they are not. Experience communicating technical knowledge to both technical and non-technical audiences, including explaining what caused an issue and how to avoid it. Experience creating documentation or training content that people actually used — help articles, runbooks, onboarding guides, internal wikis or video walkthroughs. A formal enablement title is not required; evidence that you can explain something complicated clearly in writing is. Comfort delivering training and onboarding directly to users, whether that is a live session, office hours or a recorded walkthrough, and interest in doing more of it. Knowledge of customer service best practices and experience supporting and resolving software issues. Experience with RAG systems, AI knowledge bases or prompt/context engineering is a strong plus—this person will help train and improve our AI support. While not necessary, industry experience in consumer goods, retail or supply chain is a plus. Effective time management including the ability to handle multiple customer inquiries simultaneously, organize, and prioritize.

## Role Specifics

Role is a hybrid role based in Washington DC. Hybrid is defined by our company as 3+ days/week in the office when not on vacation. Remote employees will not be considered for this role.

## About Alloy.ai

## Company Overview
- **One-liner**: Alloy.ai provides a cloud-based demand and inventory control tower that helps consumer goods brands gain real-time visibility into their supply chain, reduce stockouts, and optimize inventory.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2016
- **Founders**: Evan Goldenberg, Joel Beal, Roberto Carli, Zack Reynolds

## Core Business
- **Primary industry/industries**: Supply Chain Analytics, Retail Technology, Consumer Goods SaaS
- **Target customers**: B2B, mid-market to Fortune 500 consumer goods brands (e.g., Crayola, Bic, Valvoline, Bosch, Melissa & Doug, Ferrero)
- **Mission or purpose statement**: To help consumer goods brands sell more products, save time, and solve complex supply chain challenges by making products available where and when they are most needed.

## Products & Services
- **Alloy Intelligence**: A POS and inventory analytics solution that helps consumer goods companies reduce stockouts and excess inventory costs.
- **Integration**: Automates the real-time collection, cleansing, and enrichment of data from internal systems and partners via 850+ pre-built connectors.
- **Modeling**: Harmonizes disparate data across systems to create a unified view of the supply chain from manufacturing to consumer.
- **Prediction**: Uses predictive analytics and forecasting engines to anticipate stockouts and predict demand.
- **Sense. Predict. Respond.**: An early warning system for demand and supply imbalances using daily SKU-store level data.
- **Point of Sale Trends**: A workflow that identifies areas of demand fluctuation and provides insights for addressing root causes.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private company)
- **Key Metric**: Total Funding (Series A) — exact amount not disclosed on Crunchbase, but the company is described as "well-funded"
- **Notable Investors/Partners**: Not publicly listed in detail, but the company has completed a Series A round and is trusted by Fortune 500 brands like Ferrero, Crayola, Bic, Valvoline, Bosch, and Melissa & Doug.
- **Growth Signals**: Customers routinely achieve a 35%+ reduction in out-of-stocks, a 5%+ bottom-line impact, and millions in incremental orders. The company has expanded to offices in San Francisco, Denver, Vancouver, Toronto, Washington D.C., and Berlin, indicating strong geographic growth. Headcount is between 51-100 employees.

## Competitive Advantages
- **850+ Pre-built Connectors**: A massive data integration moat that makes it easy for brands to plug into Alloy.ai's platform, creating high switching costs.
- **Daily SKU-Store Level Insights**: Provides granular, near-real-time visibility that competitors often cannot match, allowing rapid response to demand shifts.
- **Proven ROI**: Demonstrable, quantifiable results (35% reduction in stockouts, 5%+ bottom-line impact) create a strong value proposition for new customers.
- **Purpose-Built for Consumer Goods**: Unlike generic analytics platforms, Alloy.ai is specifically designed for the complexities of CPG supply chains, including 40-year-old data standards and labor-intensive manual processes.

## Strategic Focus
- **Deepening Platform Capabilities**: Continuing to build out predictive analytics and AI-powered features (e.g., forecasting, anomaly detection) to move from "sense and respond" to "predict and act."
- **Geographic Expansion**: Growing its presence in Europe (Berlin office) and Canada (Vancouver, Toronto) to serve a global customer base.
- **Scaling Customer Success**: Investing in enterprise engagement managers to ensure large customers achieve maximum value from the platform.
- **Data Network Effects**: As more brands and retailers connect, the platform's data models and predictions become more powerful, creating a defensible network effect.

## Why Work Here
- **Culture**: Emphasizes open, asynchronous communication, individual ownership, and a just-in-time management style. Engineers are given deep context on customer problems and are expected to ship fast. The team hails from successful startups, leading tech companies, and Fortune 100 enterprises.
- **Remote/Hybrid/Office Policy**: Hybrid and remote options available. Offices in San Francisco (HQ), Denver, Vancouver, Washington D.C., and Berlin. The company describes itself as a "distributed organization across three sites."
- **Notable Perks**: Flexible leave policy, competitive health insurance, professional development budget, equity compensation, parental leave, 401K/RRSP matching, and transit benefits for hybrid employees.
- **Engineering Culture**: Engineers work on complex, rewarding problems spanning data processing (terabytes of data), supply chain modeling, and building intuitive applications. Regular knowledge sharing sessions and hackathons are part of the culture. The interview process gives candidates a hands-on glimpse of the company's tech stack.

## Sources
1. [alloy.ai](https://alloy.ai/careers)
2. [alloy.ai](https://alloy.ai/about-us)
3. [jobs.lever.co](https://jobs.lever.co/alloy)
4. [crunchbase.com](https://www.crunchbase.com/organization/alloy-3)
5. [alloy.ai](https://alloy.ai/engineering)

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