Jobs at Stord

Manage relationships with Stord Parcel customers as their primary liaison, supporting onboarding, system integrations, domestic parcel strategy, carrier diversification, delivery performance, and business reviews. Analyze shipping KPIs, costs, invoices, and accounts receivable while resolving financial discrepancies. Partner with Operations, Product, and Engineering to address customer needs and influence the parcel technology roadmap.

Build and own internal platform services that increase engineering velocity across Stord. Responsibilities include unifying product capabilities into shared services, enabling product-team integrations, building agent-ready infrastructure and MCP integrations, developing tooling and golden paths, improving developer experience, and measuring organizational impact. The role requires high autonomy, strong platform depth, practical agentic development experience, CLI-native workflows, product-oriented problem solving, and collaboration with engineering leadership and SRE.

Lead Stord’s SDET function by establishing test architecture, framework standards, CI-gated automation, and AI-assisted test generation. Build an API-first E2E testing framework spanning web UI, APIs, and Kafka eventing, with resilient handling of asynchronous workflows. Create coverage, regression, load, and performance testing infrastructure; partner with SRE on test environments; and hire, develop, and set the technical bar for the SDET team.

Own product vision, strategy, and roadmap; convert ambiguous operational and commerce problems into clear requirements; partner with engineering and design to ship features quickly; define business-linked metrics; engage customers and stakeholders; and get close to operational realities (warehouses, carriers, checkout) to ensure product quality and impact.

Embed with internal teams to identify high-leverage manual workflows and build production-grade agentic AI systems, integrations, and automation (LLM-powered interfaces, observability, APIs, dashboards) that reduce manual effort across CX, finance, ops, and logistics.

Seeking a Senior Elixir Engineer to develop scalable systems and contribute to technical decisions within product groups, focusing on Elixir and cloud technologies.

Own full-cycle recruiting for Finance and SG&A roles, including sourcing, screening, coordination, offer negotiation, and closing. Partner with Finance leaders to define hiring needs, assess accounting and finance talent, build pipelines, monitor recruiting metrics, improve processes, and deliver a strong candidate experience. Use market insights and recruiting data to support scalable, equitable hiring practices in a fast-growth environment.

Lead end-to-end experimentation pipeline for Stord Labs, coordinating robotics, AI, vendors, engineering, and operations to validate and scale logistics innovations into production pilots and enterprise rollouts, develop deployment playbooks, and manage co-funded customer pilots and executive demonstrations.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Own full-cycle recruiting for product, data, and engineering roles: source passive candidates, screen technical and product fit, partner with hiring leaders, manage pipeline metrics, improve processes, and close high-impact hires while ensuring a strong candidate experience.

Lead cross-functional internal systems programs including tooling rollouts, migrations, automation, and SOC audit readiness. Build roadmaps, run reviews, create playbooks, manage vendors and stakeholders, and deliver projects on time with strong communication and execution.

Lead and scale Revenue and Billing Operations for a multi-service 3PL platform. Own end-to-end billing, revenue recognition (ASC 606), financial reporting, systems integration (WMS/TMS/ERP/billing), automation and AI adoption, cross-functional alignment, controls, tax compliance, and build a high-performing team to ensure accurate, scalable revenue capture and margin visibility.

Lead design and delivery of an egocentric video data product: capture rigs, edge processing, dataset pipelines, VLM-assisted annotation, and production-ready perception models (detection, tracking, segmentation, depth/3D reconstruction, and 6DoF pose estimation). Operate and scale warehouse capture programs and own model training, evaluation, optimization, and deployment.

Senior individual contributor owning complex end-to-end ML problems for supply chain and consumer applications. Build and deploy predictive models (demand forecasting, delivery ETA, recommendations), embed with engineering teams, define MLOps standards, and advise leadership on data science strategy and investments.

Own quality engineering for Commerce: run structured manual QA, build E2E automation (storefront, checkout, brand portal), wire tests into CI, define Shopify-specific compatibility playbooks, set quality metrics and gates, participate in planning and spec reviews, and lead the teamto shift coverage left.

The Staff Software Engineer will lead technical initiatives, drive quality code, mentor engineers, and work on scalable systems in a high-impact team environment.

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

Own and operate scalable infrastructure on GCP (GKE, Cloud Run, AlloyDB); author Terraform modules; manage containerized workloads; build observability in Datadog; design CI/CD in GitHub Actions; automate operational workflows; lead incident response and post-mortems; partner with engineers to improve reliability, cost, and automation.

Lead and build a new Embodied AI data business: win initial customers, define data products, stand up warehouse capture operations, build data pipelines and quality processes, hire and lead a senior team, and own the P&L.