Senior Software Engineer, AI

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission.

By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.

With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.

Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.

Stord is building the operating system for the modern supply chain — a unified platform handling Order Management, Warehouse Management, Transportation, and Consumer Experience for brands doing over $10B in commerce annually. AI is not a future roadmap item here. It is actively reshaping how we operate — and LLM-powered features and autonomous agents are at the center of that transformation.
This role is for engineers who have built and shipped AI-powered products in production — not engineers who are curious about AI. You will design and build the agent frameworks, LLM-powered features, and backend services that bring AI capabilities into daily use by hundreds of logistics operations. You will work directly with our Director of AI Products and partner with Data Scientists and ML Engineers to move fast from model to product.
If you are the kind of engineer who has already shipped LLM-powered features, who gets excited about what agentic AI can do in a complex operational domain, and who wants to define the AI foundation of a platform at scale — this role was built for you.

Why This Role

• Direct line from your work to shipped AI features powering real logistics operations

• Greenfield opportunity: you will shape how AI — including agents and LLM-powered workflows — is integrated across the platform, not inherit legacy patterns

• Collaborate closely with Data Scientists and ML Engineers — this is a full-stack AI team, not siloed experimentation

• Opportunity to define internal standards and tooling that other engineers build on top of

• Work at a company where AI investment is a board-level mandate, not a pet project

What You'll Build

This is a sample of what you'll work on — the scope will evolve as we grow and as you help shape what's next.

LLM-Powered Features and Agents

• Conversational AI and agentic workflows for logistics operators and brand customers

• LLM-powered features using OpenAI, Anthropic Claude, and Cloudflare Workers AI — with proper prompt engineering, tool use, rate limiting, fallback handling, and cost controls

• Agent frameworks that orchestrate multi-step AI workflows across supply chain domains

• Recommendation engines that surface actionable intelligence to operations teams

Production AI Features

• Demand forecasting APIs that connect ML model outputs to inventory management workflows

• Intelligent routing services that leverage ML predictions for logistics optimization

• Real-time anomaly detection pipelines for supply chain monitoring

AI Platform Infrastructure

• Fault-tolerant Node.js services that consume predictions from Modal.com, Vertex AI, and other ML platforms

• Real-time data pipelines feeding ML models at production scale

• Developer abstractions that make AI capabilities easy for product engineers to integrate

• Caching, optimization, and serving strategies for low-latency inference

• Observability, alerting, and experimentation infrastructure for AI features

Cross-Functional Impact

• Partner with the Director of AI Products on technical strategy and architecture decisions

• Work with Data Scientists to translate model requirements into production-ready integration contracts

• Support product teams in implementing AI features within their domains

• Mentor other engineers on AI integration patterns and best practices

What We're Looking For

Required

• LLM and agent development (2+ years): Proven production experience building and deploying LLM-powered features — not just API integration, but full product delivery including prompt engineering, tool use, agent orchestration, and reliability at scale.

• TypeScript / Node.js (3+ years): Production experience building scalable backend services. This is your primary environment.

• AI frameworks: Hands-on experience with LangChain, LangGraph, or equivalent agent orchestration frameworks.

• ML platform integration: Hands-on experience consuming predictions from Modal.com, Vertex AI, or similar inference platforms.

• Distributed systems: Fault tolerance, async patterns, message queues (Kafka or equivalent), event-driven architecture.

• API design: RESTful and event-driven integration experience — both building and consuming.

• Database: Advanced SQL with PostgreSQL. You can write a query that matters.

• Cloud: Hands-on GCP, AWS, or Azure. GCP preferred given our stack.

• High agency: You operate with minimal direction. You identify the right problem, propose solutions, and drive to done.

• Product mindset: You optimize for user impact, not just code elegance. Reliability and delivery matter to you.

Strongly Preferred

• Vector databases and semantic search (Pinecone, Weaviate, pgvector, or equivalent)

• Feature stores and real-time ML serving patterns

• Cloudflare Workers / edge inference experience

• A/B testing and experimentation infrastructure

Nice to Have

• Elixir / Phoenix — we run a mixed stack and cross-pollination is valued

• Event sourcing patterns

• Contributions to open source AI, TypeScript, or Node.js projects

• Domain experience in logistics, supply chain, or operations-heavy B2B contexts

What Success Looks Like

In your first 30 days, you have made a meaningful contribution to production — not a small fix, but something that moves the product. You understand our stack, our AI architecture, and our roadmap, and you have already started shaping how we approach problems. By 90 days, you are a trusted technical voice on the AI team, driving architecture decisions and setting patterns that others follow. By six months, you have shipped multiple AI-powered features end to end, you are raising the bar for how AI is built and deployed at Stord, and you are actively mentoring others on what good looks like.

About Stord

Stord is a cloud-based supply chain platform that enables brands to compete and grow through end-to-end logistics solutions. We process over $10B in commerce annually and operate across Order Management (OMS), Warehouse Management (WMS), Transportation Management (TMS), Consumer Experience, and Demand Planning. We are backed by leading investors and are rapidly scaling our engineering organization to match our ambitions.