Stord is a leading innovator in the consumer experience sector, dedicated to providing seamless checkout solutions through delivery for top brands. As we embark on an exciting growth trajectory, aiming to double our revenue in the next 18 months, we are expanding our teams and looking for passionate experts to join us in achieving this ambitious mission.
By merging advanced commerce-enablement technology with high-volume fulfillment services, Stord empowers brands to compete effectively against retail giants. Our platform processes over $10 billion in commerce annually, offering fulfillment, warehousing, transportation, and a suite of operator-built software including OMS, Pre- and Post-Purchase, and WMS systems. We aim to level the playing field for brands striving to deliver superior consumer experiences at scale.
With Stord, brands can enhance cart conversion rates, boost unit economics, and cultivate lasting customer loyalty. Our comprehensive solutions integrate best-in-class omnichannel fulfillment and shipping capabilities with cutting-edge technology to ensure prompt shipping, trustworthy delivery commitments, streamlined access to numerous channels, and improved profit margins on every order.
Hundreds of leading DTC and B2B companies, such as AG1, True Classic, Native, Seed Health, quip, goodr, and Sundays for Dogs, trust Stord to deliver exceptional consumer experiences consistently. Stord is headquartered in Atlanta, with facilities across the United States, Canada, and Europe. We are backed by prestigious investors, including Kleiner Perkins, Franklin Templeton, Founders Fund, and Salesforce Ventures.
Stord is revolutionizing logistics through our cloud-based supply chain platform. Our AI team is crafting next-generation features such as Demand Planning, predictive analytics, and intelligent automation, leveraging traditional ML models and pioneering LLM capabilities. We are looking for an experienced Elixir engineer who views programming languages as versatile tools and can seamlessly integrate AI features into our core platform.
In this role, you will be a vital member of our AI team, working closely with the Director of AI Products to design and develop AI-powered functionalities. You will collaborate with Data Scientists to define model requirements and partner with ML Engineers to ensure smooth integration between our ML infrastructure and core services. This position offers the opportunity to directly influence the integration of AI into our logistics platform, including building crucial features like demand forecasting APIs and intelligent routing services.
Your Responsibilities :
- Develop robust Elixir services that utilize ML predictions from various platforms.
- Integrate existing or new products with edge-based inference as needed.
- Create resilient systems that can manage service failures and provide intelligent fallbacks.
- Implement caching and optimization strategies for efficiently serving AI features.
- Build real-time data pipelines using Kafka and Elixir for feeding ML models.
- Develop Demand Planning services that align forecasting models with inventory management.
- Create intelligent routing systems that apply ML predictions for optimal logistics solutions.
- Establish real-time anomaly detection services for supply chain monitoring.
- Implement AI-enhanced recommendation engines for logistics improvements.
- Design and build APIs for LLM integration, ensuring proper rate limiting and error management.
- Create distributed systems capable of processing millions of AI-driven logistics operations.
- Build comprehensive monitoring, alerting, and observability solutions.
- Develop tools and abstractions that facilitate easy AI capability integration for other engineers.
- Manage configuration and feature flagging for experimental setups.
- Optimize performance and cost efficiency throughout the platform.
- Collaborate on architecture decisions and technical strategies with the Director of AI Products.
- Work alongside Data Scientists to comprehend model inputs, outputs, and constraints.
- Partner with ML / Data Engineers to guarantee seamless model deployment.
- Assist product teams in incorporating AI features into their projects.
- Mentor fellow engineers on AI tool usage and integration best practices.
Qualifications :
Proven expertise in Elixir / Phoenix (2+ years) with a track record of building and scaling production systems.Strong TypeScript skills (2+ years) with the ability to select the most effective tools for specific tasks.Deep understanding of Distributed Systems, including fault tolerance and OTP patterns.Experience in API Design & Integration, building and consuming RESTful APIs and event-driven architectures.Advanced database skills, especially with PostgreSQL; familiarity with AlloyDB is preferred.Experience with message queues like Kafka, RabbitMQ, or similar platforms.Hands-on experience with cloud platforms such as GCP (preferred), AWS, or Azure.Track record of optimizing high-throughput, low-latency systems.Essential Soft Skills :
Production mindset focused on reliability and user impact over perfection.Systems thinking with an understanding of how AI features integrate into broader architectures.Strong communication skills to convey technical decisions and trade-offs to diverse audiences.A collaborative attitude that thrives in team environments.Learning agility and adaptability to evolving AI / ML technologies and tools.Preferred Experience :
Experience with LLM integration (e.g., OpenAI, Anthropic Claude).TypeScript proficiency, as our work spans across Elixir, TypeScript, and Python.Familiarity with edge platforms like Cloudflare Workers / AI.Knowledge of event sourcing methodologies.Insight into feature stores and real-time ML serving.Experience using Modal.com, Vertex AI, or related ML platforms.Understanding of logistics, e-commerce, or supply chain sectors.Experience with GenAI applications and prompt engineering.Acquaintance with vector databases and semantic search techniques.Contributions to open source projects in Elixir, TypeScript, or AI.Experience with A / B testing and experimentation frameworks.