The Consumer Experience Company | Fulfillment, Last-Mile Delivery, & Technology
Senior Software Engineer, AI
Location
United States + 1 moreAll locations: United States | Canada
Posted
82 days ago
Salary
0
Seniority
Senior
Job Description
Senior Software Engineer, AI
Stord
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.
Job Requirements
- 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.
Benefits
- 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 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.
Related Guides
Related Job Pages
More AI Engineer Jobs
Lead AI & Automation Engineer - Security & Privacy (Federal Healthcare) Remote | Occasional Travel to Washington, DC Supporting Federal Healthcare Security & Privacy Programs Full-Time Salary: $145,000 - $160,000 annually (based on experience) Mission Impact This role supports modernization of security, privacy, and compliance operations within a federal healthcare environment by implementing advanced Artificial Intelligence (AI), machine learning, and automation technologies. Your work will help protect sensitive healthcare data (PII/PHI) while improving operational efficiency and enabling faster response to evolving cyber threats. Position Overview Fathom Management, Inc. is seeking a Lead AI & Automation Engineer to design and deploy AI-driven security and privacy automation solutions supporting federal healthcare programs. This role combines AI engineering, machine learning, cybersecurity analytics, and automation development to enhance security monitoring, compliance validation, and privacy operations. The ideal candidate will have hands-on experience building generative AI solutions, RAG-based chatbots, and machine learning models integrated with SIEM platforms such as Splunk. You will collaborate with security teams, compliance stakeholders, and engineering teams to develop intelligent systems that automate document review, detect security anomalies, and support responsible AI governance. Technology Stack Generative AI, Retrieval-Augmented Generation (RAG), Machine Learning, Splunk SIEM, SOAR Platforms, CI/CD Pipelines, Python, Automation Frameworks, NIST/FISMA Compliance, HIPAA Security Standards Key Responsibilities AI Engineering & Automation Development - Design and implement AI-powered automation solutions to improve security and privacy operations. - Build and manage an Agile AI development framework, including sprint planning, backlog refinement, and CI/CD pipelines. - Develop and maintain an AI-powered RAG chatbot that supports real-time security and privacy inquiries. Machine Learning & Security Analytics - Implement machine learning models within SIEM platforms (e.g., Splunk) to detect: - security anomalies - insider threats - emerging attack patterns - Deploy AI-driven analytics that improve threat detection and incident response. AI-Driven Compliance & Document Automation - Develop AI tools to automate document review and classification for PII/PHI exposure. - Build automated workflows that validate compliance with NIST, FISMA, HIPAA, and internal governance policies. - Use generative AI technologies to: - Summarize Security Incidents - Automate workflow documentation - Generate training materials - Accelerate policy and SOP creation. Responsible AI Governance - Support AI governance frameworks, including model monitoring, validation, and risk assessment. - Ensure all AI tools comply with Section 508 accessibility standards and WCAG 2.1 AA guidelines. - Develop documentation and training supporting responsible and secure AI usage in federal environments. Required Qualifications - Hands-on AI/ML engineering experience, including generative AI, RAG architectures, and predictive modeling. - Experience integrating machine learning models into SIEM or security analytics platforms such as Splunk. - Strong experience with automation engineering, CI/CD pipelines, and version control systems. - Familiarity with federal cybersecurity and privacy frameworks, including: - NIST - FISMA - HIPAA - Understanding of Section 508 accessibility standards and WCAG 2.1 AA requirements. - Strong communication and collaboration skills working with security, compliance, and engineering teams. - Experience working in regulated industries or federal environments is preferred. Minimum Requirements - Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field - Minimum 5 years of professional experience in AI engineering, automation, cybersecurity analytics, or related disciplines Benefits & Career Growth At Fathom Management, Inc., we provide a comprehensive benefits package designed to support employee well-being, financial security, and professional development. Employee Benefits Include - Paid vacation, sick leave, and company holidays - Medical, dental, and vision insurance - Life insurance coverage - Short-term and long-term disability insurance - 401(k) retirement plan with company match and immediate vesting - Military leave benefits - Training and professional development opportunities - Tuition reimbursement programs - Employee wellness initiatives - Commuter benefits - Additional voluntary benefits About Fathom Management, Inc. Fathom Management, Inc. supports federal healthcare and technology modernization initiatives that improve security, privacy, and digital service delivery. Our teams specialize in AI engineering, cybersecurity analytics, digital transformation, and program delivery supporting government agencies responsible for protecting sensitive healthcare information. Joining Fathom Management means contributing to mission-critical programs that safeguard healthcare data and improve public-sector technology capabilities. Equal Employment Opportunity (EEO) Statement Fathom Management, Inc. is committed to providing equal employment opportunities to all employees and applicants. All employment decisions-including recruiting, hiring, training, promotion, compensation, benefits, and termination-are made without regard to race, color, religion, creed, national origin, sex, age, marital status, sexual orientation, gender identity, citizenship status, veteran status, disability, or any other characteristic protected by applicable federal, state, or local law.
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join Join our dynamic Research Team, which provides Airbnb with actionable insights to inform strategic decisions. You’ll be part of Innovation Insights, a division of Research that delivers insight into cultural trends, the competitive landscape, key audience segments, and new growth opportunities to help shape the future of Airbnb. Innovation Insights is also at the forefront of accelerating research and delivering critical insights using custom-built, cutting-edge AI tools and methods. The Difference You Will Make As AI-Enabled Insights Lead, you will develop and run AI-powered analyses to uncover actionable insight into travelers and travel trends globally, current and prospective Airbnb guests, and current and prospective Airbnb hosts. You will partner with stakeholders across the Research, Strategy, Product, Engineering, Data Science, Analytics and Marketing teams. Your work will grow our competitive advantage via trailblazing, AI-driven research and insights that fuel Airbnb innovation. A Typical Day - Collaborate with a best-in-class research team to deliver insights that impact business strategies. - Work with internal and cross-functional partners to identify opportunities to drive research efficiencies and business impact. - Lead and collaborate on building innovative AI-powered methods, including leveraging third-party and in-house tools/infrastructure to build AI-orchestrated pipelines customized for insights-driven analyses. - Analyze large scale structured and unstructured data from internal sources (e.g., guest searches and reviews), primary research (e.g., interviews conducted globally at scale), and external sources (e.g., social media or chatbot conversations). - Combine NLP with advanced data analysis and statistical modeling to uncover relationships, test hypotheses and extract new insights. - Augment the team’s already advanced use of AI as a complement to, and catalyst for, human insights and expertise. - Manage the team’s program for identifying third-party AI tools that add value and extend our capabilities. - Learn from, and share with, the Airbnb technical community. Your Expertise - Advanced degree in a quantitative human-oriented field preferred (social science, cognitive science, psychology, neuroscience, economics, etc.) and 5+ years industry experience. - Expertise in using Python, SQL and agentic coding tools such as Claude Code, Codex, and/or Cursor. - Track record of success in leveraging NLP for the purpose of uncovering insights into human motivations and behaviors. - Technical expertise in cutting-edge AI techniques and building AI-orchestrated pipelines to analyze complex data. - History of strong communication and collaboration with cross-functional partners, including partners with and without technical backgrounds. - Demonstrated willingness to continue learning, adopt technologies/approaches, and collaborate and share with the technical community. - Ability to balance a detail-oriented, hands-on approach with creative, “outside-the-box” thinking. - Growth-minded, solutions-oriented approach with a history of driving projects from idea to impact. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $176,000—$220,000 USD
AI Engineer Trainee, Non-Tech Backgrounds Welcome
Flatiron SchoolLaunch a career with in-person or online courses in Product Design, Data Science, Software Engineering or Cybersecurity.
• Complete Flatiron School’s Software Engineering (full-time) and Data Science (part-time) bootcamp programs • Contribute to real software projects during a paid apprenticeship with an employer partner • Collaborate in sprint-based workflows and participate in code reviews • Build a portfolio of production-level work
AI Engineer – Accelerated Immersive Program
Flatiron SchoolLaunch a career with in-person or online courses in Product Design, Data Science, Software Engineering or Cybersecurity.
• Attend and complete the part-time Data Science & AI Bootcamp as part of the apprenticeship • Contribute to software projects for your host company • Write clean, maintainable and testable code using modern frameworks and tools • Collaborate in sprint-based workflows and participate in code reviews • Support feature development, debugging, documentation, and QA processes • Build your portfolio of production-level work while growing your technical and collaborative skills • Receive ongoing mentorship from senior developers and product leaders
