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.
The Senior Engineering Manager, AI leads a cross-functional team building AI-powered capabilities for both internal productivity tools and customer-facing products. This role is accountable for predictable delivery, team development, and translating AI opportunities into shipped products that drive business value. The team operates within Stord's established architectural patterns while pushing the frontier of AI/ML applications in logistics and supply chain.
Key Responsibilities
Team Leadership & Development
Manage performance, career growth, and development for cross-functional team
Conduct regular 1:1s, performance reviews, and provide actionable feedback
Build team culture that balances innovation with delivery accountability
Recruit and onboard additional team members as team scales
Develop technical capabilities across software engineering, data science, and machine learning disciplines
Delivery Management & Execution
Own sprint planning, execution, and predictable delivery of AI initiatives
Establish clear visibility into team capacity, work in flight, and blockers
Maintain alignment with Stord's standard R&D processes
Balance internal tooling development with customer-facing AI features
Coordinate dependencies with other engineering teams and product stakeholders
Technical & Product Strategy
Translate AI opportunities into concrete, deliverable product initiatives
Make informed technical trade-offs between speed, quality, and innovation
Collaborate with Principal Engineers on technical direction and architectural patterns
Evaluate emerging AI/ML technologies and frameworks for team adoption
Ensure AI solutions are production-quality, scalable, and maintainable
Cross-Functional Collaboration
Partner with Product Management to prioritize AI roadmap and define success metrics
Work with Engineering leadership to align AI initiatives with organizational technical direction
Coordinate with other Engineering Managers on integration points and shared infrastructure
Communicate progress, blockers, and trade-offs transparently to stakeholders
Evangelize and propagate the use of AI through the engineering organisation
Required Experience & Capabilities
Management Experience:
3+ years engineering management experience leading teams of 5+ engineers
Proven track record managing cross-functional teams with multiple disciplines (software engineering, data science, ML)
Experience at multiple companies demonstrating adaptable leadership across different organizational contexts
Strong delegation skills with history of developing team members and multiplying impact through people
Established ability to deliver predictably while maintaining team morale and technical quality
Technical Background:
Hands-on experience building AI/ML products or systems (not purely theoretical)
Understanding of modern AI/ML development lifecycle from experimentation to production
Sufficient technical depth to evaluate trade-offs, guide architectural decisions, and earn team credibility
Familiarity with MLOps, model deployment, and production ML systems
Experience working in product-focused engineering organizations (not pure research)
Organizational Skills:
Strong process discipline: sprint planning, delivery tracking, stakeholder communication
Ability to balance innovation with pragmatic delivery constraints
Clear, transparent communication style with both technical and non-technical audiences
Navigate ambiguity and set direction when requirements are evolving
Build alignment across teams and functions without formal authority
Domain Context (Nice to Have):
Experience in logistics, supply chain, or operations-heavy industries
Background with Elixir or TypeScript (Stord's primary stack)
Understanding of AI applications in B2B or enterprise contexts