A

Alloy AI

SaaS platform for supply chain visibility

GTM Engineer - Sales

Full-TimePosted on 10/15/2026
$90k - $120k/yr
Junior, Mid
Vancouver, BC, Canada
Hybrid
Sales & Account ManagementSales Development Representative

About the job

Requirements
  • A technical foundation in computer science, engineering, data, or a quantitative area, gained through a degree or equivalent work, and 1 to 5 years of experience.
  • At least 1 year of writing production code, preferably in Python or TypeScript, with the ability to build third-party API integrations handling authentication, pagination, rate limits, and retries without supervision.
  • Fluency with agent harnesses such as Claude Code, Antigravity, or Codex.
  • Experience automating another person's workflow and the ability to describe the before-and-after process.
  • Evidence of self-directed building through side projects, automations, or tools created independently.
  • Interest in why buyers buy and what makes outreach effective.
  • Ability to explain technical work clearly to Sales and Marketing and comfort being measured on pipeline.
Responsibilities
  • Automate qualification and first responses for Contact Us inquiries, demo requests, and partner leads, with a human handoff for suitable prospects.
  • Route each inbound lead to the appropriate owner with an enriched, researched brief attached.
  • Track speed-to-lead and establish the service-level agreement used to measure it.
  • Run signal-based email and other outreach campaigns end to end, including list building, enrichment, messaging, and sequencing.
  • Manage email deliverability, including domains, warmup, suppression lists, and send limits.
  • A/B test messaging and report results by segment.
  • Deliver a daily prioritized call list for each account executive and sales development representative, including who to call, why now, direct dial, and a talk track.
  • Route engaged campaign replies to sales development representatives for follow-up.
  • Capture call activity, including dials, connects, and meetings, to make phone performance visible.
  • Build and maintain integrations between Salesforce, HubSpot, enrichment tools, and sequencing tools used by the automations.
  • Own the fields, objects, and routing rules that the automations read and write.
  • Track output through source attribution for automation-sourced opportunities and response times.
Desired Qualifications
  • Exposure to Salesforce, HubSpot, Clay, Apollo, or similar tools.
  • Experience in sales, sales development, growth, or marketing operations.
  • Interest in consumer packaged goods, retail, or supply chain.
  • Startup experience.

About the company

A

Alloy AI

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cbWebsite

Alloy AI runs a subscription-based SaaS platform for consumer goods brands to manage supply chain and sales operations. Its system acts as a real-time control tower that provides end-to-end visibility of inventory and shipments and surfaces analytics for sell-in (retailer demand) and sell-through (consumer purchase) so brands can react to current demand. Users access dashboards and insights to optimize inventory, shipments, and marketing investments, which helps reduce working capital, minimize waste, and strengthen retailer partnerships while safeguarding market share. The platform differentiates itself by offering integrated, real-time visibility and analytics focused specifically on both supply chain and sales stages (not just logistics) to enable proactive demand response. Alloy AI’s goal is to bridge planning and execution for consumer goods brands, enabling faster, data-driven decisions across the entire go-to-market chain and ultimately improve performance in retail channels.

Company Size

51-200

Company Stage

Series A

Total Funding

$15.3M

Headquarters

San Francisco, California

Founded

2016

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Simplify's Take

What believers are saying

  • Alloy.ai launched Replenishment and Performance Reporting agents in May 2026, expanding product depth.
  • The February 2026 Liftlab partnership opens a new marketing-measurement budget category.
  • Existing customers cite 35% out-of-stocks reduction and 35% forecast-accuracy gains at Ember.

What critics are saying

  • Kinaxis and o9 are shipping agentic supply-chain tools, compressing Alloy.ai's differentiation window.
  • Customer proof still leans on testimonials from Ferrero, BIC, Ember, and Melissa & Doug.
  • If AI Agents fail to drive measurable ROI, consumer brands will standardize on spreadsheets.

What makes Alloy AI unique

  • Alloy.ai unifies 450-plus retailer, ERP, and distributor feeds into SKU-store decisions.
  • Its May 2026 AI Agents automate replenishment and performance reporting across consumer brands.
  • Liftlab partnership ties media spend to retail sales at SKU, retailer, and location levels.

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Benefits

  • Hybrid Work Options
  • Paid Vacation

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

4%

2 year growth

-1%
SeaPRwire
May 25th, 2026
Alloy.ai launches AI Agents designed to help consumer brands reduce stockouts and supply chain costs.

Alloy.ai launches AI Agents designed to help consumer brands reduce stockouts and supply chain costs. SAN FRANCISCO, CA - 25/05/2026 - (SeaPRwire) - As consumer brands face increasing pressure to manage inventory volatility, retailer compliance requirements, and fragmented commerce data, many organizations are turning to artificial intelligence to improve operational decision-making. Alloy.ai, a provider of commerce intelligence solutions for consumer brands, announced the launch of two new AI Agents aimed at helping sales and supply chain teams automate critical workflows and respond faster to revenue risks across retail networks. The company introduced a Replenishment AI Agent and a Performance Reporting AI Agent as the first additions to a broader AI automation roadmap. Alloy.ai also confirmed that a Trade Promotion AI Agent and a Forecast Adjustment AI Agent are expected to become available in the third quarter of 2026. According to Alloy.ai, consumer brands frequently lose significant revenue opportunities because operational data remains fragmented across retailers, ecommerce platforms, distributors, and internal systems. Even after data is consolidated, teams are often overwhelmed by the volume and complexity of information required to make timely decisions. The company said this operational lag can contribute to OTIF (On-Time In-Full) penalties, stockouts, expedited freight costs, and retailer chargebacks. Alloy.ai stated that its AI Agents are designed to continuously monitor every SKU across retail, ecommerce, and distribution channels while proactively preparing recommended actions before operational issues impact financial performance. Joel Beal, Founder and CEO of Alloy.ai, said many brands have historically viewed supply chain inefficiencies and retailer penalties as unavoidable operational costs. He noted that fragmented data environments and overloaded teams have traditionally prevented organizations from identifying and addressing issues quickly enough to avoid financial impact. According to Beal, the new AI Agents are intended to shift organizations from reactive problem-solving toward automated, execution-ready decision support. The newly launched Replenishment AI Agent is designed to help replenishment teams manage inventory performance across both major and secondary retail accounts. The system monitors product demand trends, identifies locations where inventory levels may not meet expected demand, calculates recommended replenishment quantities, and generates approval-ready communications supported by relevant data insights. The company said the automation aims to reduce the manual workload associated with navigating retailer portals, compiling spreadsheets, and tracking account-specific inventory issues. Alloy.ai noted that the technology is intended to provide broader retail coverage while enabling teams to prioritize strategic decision-making. Peter Choi, Sales Analyst at Melissa & Doug, stated that replenishment planning has historically required teams to balance attention between underperforming and high-performing products, often creating operational blind spots. He added that the AI Agent helps surface risks that teams may not otherwise have the bandwidth to identify manually. Alloy.ai also introduced its Performance Reporting AI Agent, which automates the process of compiling weekly commerce performance reports. The system aggregates POS data, shipment records, and inventory metrics across the company's connected commerce network before generating executive summaries that include live visualizations and narrative analysis. According to Alloy.ai, the technology is intended to help organizations reduce the amount of manual reporting work required each week while accelerating access to actionable business insights. Matt DePaolo, Omnichannel Growth & Strategy Team Lead at BIC, said the reporting automation could significantly improve workflow efficiency for lean teams. He noted that the ability to automate data analysis and business performance summaries may substantially reduce time spent preparing for internal meetings. In addition to the new AI Agents, Alloy.ai continues to offer Lens, a generative AI chat interface that functions as an AI-powered commerce analyst. Lens allows users to query unified operational data using natural language and perform multi-dimensional analysis across sales and supply chain functions. The interface is integrated within the AI Agents, enabling users to review recommendations, refine outputs, and provide feedback in real time. The company stated that all current and upcoming AI Agents are built on Alloy.ai's unified data infrastructure, which includes more than 450 pre-built integrations across ERP systems, retailers, distributors, and ecommerce platforms. Additional AI-driven operational tools remain in development as the company expands its automation portfolio for the consumer goods sector. About Alloy.ai Alloy.ai is a commerce intelligence platform designed for consumer brands. The company consolidates data from retailers, distributors, ecommerce platforms, and enterprise systems into a unified operational view intended to support sales, inventory, and supply chain decision-making. Brands including Liquid I.V., Crayola, and Valvoline use Alloy.ai to improve demand visibility, operational efficiency, and retail execution.

Associated Press
May 19th, 2026
Alloy.ai launches AI agents to help consumer brands recoup billions lost to avoidable supply chain costs

Alloy.ai, a commerce intelligence platform for consumer brands, has launched two AI agents designed to help companies avoid revenue losses from operational inefficiencies. The San Francisco-based startup released a Replenishment AI Agent and a Performance Reporting AI Agent, with Trade Promotion and Forecast Adjustment agents planned for Q3 2026. The Replenishment Agent monitors every SKU across retail networks, identifies supply-demand gaps, and drafts approval-ready order recommendations. The Performance Reporting Agent automatically compiles weekly performance reports from POS data, shipment records and inventory levels, delivering executive briefs before meetings. The agents build on Alloy.ai's existing Lens AI interface and unified data architecture, which integrates over 450 sources including ERPs, retailers and distributors. Customers include Liquid I.V., Crayola and Valvoline.

Associated Press
Feb 12th, 2026
Alloy.ai and Liftlab partnership ties omni-channel marketing spend to in-store sales

Alloy.ai and Liftlab have partnered to help consumer brands measure marketing return on investment across digital and retail channels by connecting advertising spend to in-store sales. The partnership combines Alloy.ai's real-time point-of-sale data from hundreds of retailers with Liftlab's media measurement capabilities. Brands can now track incremental return on ad spend down to individual products, retailers and locations in real-time. Alloy.ai collects and harmonises item- and store-level retail data, whilst Liftlab analyses the complete marketing mix including digital, radio, television, print and retail activation. The solution addresses a longstanding challenge for consumer brands with significant wholesale revenue, providing unified visibility across both direct-to-consumer and brick-and-mortar performance. Alloy.ai customers typically achieve a 35% reduction in out-of-stock situations and a 5% bottom-line impact.

PYMNTS
Dec 15th, 2024
Genai At Retail: New Technology Upgrades For Inventory And Demand Forecasting

01 A lack of real-time inventory visibility and difficulties in accurately predicting shopper demand often result in overproduction, excess stock or critical shortages — all of which have a direct and detrimental impact on profitability. 02 GenAI is transforming inventory management by enabling accurate demand forecasting, optimized stock levels and streamlined replenishment processes. Solutions like Alloy.ai, Hypersonix and Maiven provide real-time tools that empower retailers to make data-driven decisions and respond swiftly to market changes. 03 If managing inventory is retail business managers’ top priority, delivering personalized shopping experiences is a close second. Offering consumers exactly what they want can drive sales, but it also demands precise control over stock levels to ensure a seamless and satisfying customer experience. Personalized offers fall flat without available inventory

PR Newswire
Mar 28th, 2024
Retail Analytics Market Worth $25.0 Billion By 2029 - Exclusive Report By Marketsandmarkets™

CHICAGO, March 28, 2024 /PRNewswire/ -- Adoption of real-time capabilities and sophisticated analytics, such as artificial intelligence, for omnichannel integration and improved customer experiences is what the Retail Analytics Market will look like in the future. Partnerships for innovation, a rising emphasis on sustainability and ethical analytics, supply chain optimisation, in-store analytics, and a focus on data privacy and security will all be critical.The Retail Analytics Market is projected to grow from USD 8.5 billion in 2024 to USD 25.0 billion by 2029, at a compound annual growth rate (CAGR) of 24.0% during the forecast period, according to a new report by MarketsandMarkets™. The Retail Analytics Market is expected to grow significantly during the forecast period, owing to various business drivers like the increasing increasing adoption of omni-channel retail strategies, exponential growth of e-commerce platforms, and proliferation of data generated through diverse channels is also responsible for driving the market's growth.Browse in-depth TOC on "Retail Analytics Market"300 - Tables75 - Figures310 - PagesDownload PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=123460609Scope of the ReportReport Metrics Details Market size available for years 2019–2029 Base year considered 2023 Forecast period 2024–2029 Forecast units USD (Billion) Segments Covered Offering, Business Function, Application, End User, and Region Geographies covered North America, Asia Pacific, Europe, Middle East & Africa, and Latin America Companies covered Microsoft (US), IBM (US), SAP (Germany), Oracle (US), Salesforce (US), MicroStrategy (US), SAS Institute (US), AWS (US), Qlik (US), Teradata (US), WNS (India), HCL (India), Lightspeed Commerce (Canada), RetailNext (US), Manthan Systems (India), Fit Analytics (Germany), Trax (Singapore), ThoughtSpot (US), RELEX Solutions (Finland), Tredence (US), Creatio (US), Solvoyo (US), datapine (Germany), Sisense (US), EDITED (UK), Retail Zipline (US), ThinkINside (Italy), Dor Technologies (US), Triple Whale (Israel), Flame Analytics (Spain), Alloy.ai Technologies (US), Conjura (UK), Kyvos Insights (US), Pygmalios (Slovakia), and SymphonyAI (US)By Software by analytics type, the predictive analytics segment to register for the largest market size during the forecast period.By software by analytics type, the predictive analytics segment is expected to register the largest market size during the forecast period. Predictive analytics software can help forecast sales volumes, identify demand fluctuations, and predict customer preferences, enabling retailers to optimize pricing strategies, allocate resources efficiently, and tailor marketing campaigns to target specific customer segments. Recent advancements in predictive analytics technology, including the integration of AI and machine learning algorithms, have further enhanced the capabilities of predictive analytics software, enabling retailers to gain deeper insights, make more accurate predictions, and drive greater business value.Request Sample Pages@ https://www.marketsandmarkets.com/requestsampleNew.asp?id=123460609By services, managed services to register for the highest CAGR during the forecast period.The managed segment of the Retail Analytics Market is growing rapidly. Managed service providers (MSPs) offer tailored solutions that cater to the unique needs and challenges of retailers, delivering insights that drive operational efficiency, enhance customer engagement, and drive revenue growth