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Order.co is the System of Action for the Office of the CFO, transforming the way businesses purchase and pay into an intuitive, B2C-like shopping experience. Order.co leverages embedded AI agents and embedded financial products to reinvent the way businesses connect with their vendors.End users enjoy a seamless, zero-training buying experience, while finance and procurement leaders gain a single platform to orchestrate how the business “should operate”. The result is an all-in-one solution that serves as a gravitational pull for spend and data, automating and eliminating procurement and finance workflows from requisition to reconciliation along the way.Order.co is on the cutting edge of B2B Agentic Commerce, poised to be the market leader in creating a more predictive, prescriptive, and personalized experience for users.Founded in 2016 and headquartered in New York City, Order.co oversees nearly half a billion in annualized spend across hundreds of customers like WeWork, SoulCycle, Lume, and [solidcore]. Order.co has raised $75M in funding from industry-leading investors like MIT, Stage 2 Capital, Rally Ventures, 645 Ventures, and more. Order.co has been proudly named a 50 to Watch by Spend Matters and a Best Place to Work by BuiltIn and Inc. Magazine.The RoleAs a Senior AI / Data Engineer, you will design, build, and maintain scalable data and AI infrastructure that powers critical business and product capabilities across the organization. You will partner closely with software engineers, analytics, product, and operations teams to deliver reliable data systems, production-ready AI workflows, and high-quality datasets that enable intelligent decision-making and automation.You bring strong software engineering fundamentals together with practical expertise in data systems, cloud infrastructure, and AI-enabled development workflows. You care deeply about reliability, maintainability, operational excellence, security and building systems that scale with the business.ResponsibilitiesData & AI Platform EngineeringDesign, build, and maintain scalable data pipelines, integrations, and AI workflowsDevelop reliable and maintainable ETL/ELT systems that support analytics, operational reporting, and AI-driven productsContribute to the architecture and evolution of the company’s data platform and AI infrastructureBuild systems and services with a focus on simplicity, iterative development, reliability, and long-term maintainabilityContinuously optimize data architecture to support evolving business and product requirementsPartner with stakeholders to translate business problems into scalable data and AI solutionsInfrastructure, Automation & ReliabilityDevelop infrastructure automation and deployment workflows to improve engineering velocity and operational consistencyImplement infrastructure as code (IaC) practices using tools such as Terraform or CloudFormationBuild and maintain CI/CD pipelines and automated testing workflowsDevelop monitoring, alerting, and observability solutions for data and AI systemsImprove reliability, scalability, and operational efficiency through automation and proactive system improvementsParticipate in incident response and operational support rotations as neededAI Enablement & Engineering ProductivityContribute to production-ready AI systems and workflows where they provide measurable business valueEvaluate and integrate AI-assisted engineering tools responsibly and pragmaticallySupport the deployment and operationalization of machine learning and AI-powered servicesHelp establish best practices for AI-assisted software development, evaluation, and operational safetyCollaboration & Technical LeadershipContribute to roadmap planning, technical design discussions, and engineering prioritizationMentor junior and mid-level engineers through code reviews, pairing, and technical guidanceCollaborate cross-functionally with Engineering, Product, Analytics, and Operations teamsCommunicate technical trade-offs, implementation details, and operational risks clearly to stakeholdersPromote engineering best practices around testing, observability, documentation, and operational excellenceQualificationsYou are motivated by accountability and ownership of outcomesYou are results-oriented and focused on delivering reliable, working systemsWriting tests is an integral part of your development processYou know how to design and build software incrementallyYou enjoy collaborating with others to solve complex technical problemsYou are collaborative, open-minded, and continuously improving your craftYou are curious and pragmatic about AI-driven solutions and apply them thoughtfully where they create real valueYou understand both the strengths and limitations of AI-assisted engineering tools and evaluate their output criticallyTechnical SkillsStrong proficiency in Python and SQLHands-on experience with data orchestration tools (preferably Airflow, Dagster, or AWS Step Functions)Proven experience building and operating AWS cloud infrastructure, particularly services such as Lambda, ECS, and SQSExperience implementing infrastructure as code using Terraform or similar toolingStrong experience designing event-driven, serverless architectures using AWS Lambda, API Gateway, EventBridge, and SQS/SNSHands-on experience working with large-scale data platforms in production environments (preferably Spark/PySpark, AWS Glue, or EMR)Strong understanding of AWS data lake technologies including S3, Glue Catalog, and Lake FormationHands-on experience with cloud data warehouses (preferably Snowflake) including schema design, performance tuning, cost optimization, and access controlExperience designing and maintaining reliable ETL/ELT pipelines and distributed data workflowsHands-on experience with SQL-based transformation frameworks such as dbt (Core or Cloud)Familiarity with CI/CD systems and tooling such as GitHub Actions or CircleCIUnderstanding of observability, monitoring, and operational best practices for data systemsStrong understanding of data security, access controls, and protecting sensitive dataExperience building automation and operational tooling using Python or similar languagesFamiliarity with production AI/ML workflows and operational considerations for AI-enabled systemsExperience using AI-assisted engineering tools (e.g., Claude Code, Codex, GitHub Copilot) responsibly to improve productivity and engineering qualityWhat Great Looks LikeA Senior Software Engineer on the Payments team who is thriving at this level demonstrates:Reliable delivery of complex work — consistently ships multi-part solutions on time with low defect ratesLow defects in owned areas — proactively monitors and improves the quality of the systems they own; that means incident-free quarters in code paths that move funds and clean reconciliation against vendor reportsMeasurable mentorship impact — engineers around you write better code because of your reviews and guidance“Someone we can depend on for the work that matters — especially the work that touches money.”Failure Modes We Screen AgainstWe actively evaluate candidates for the following anti-patterns during the interview process:Failure ModeWhat It Looks LikeStrong coder, weak ownerShips code but doesn't manage to the task — owns the merge, not the outcome; hands off and moves on without monitoring or fixing post-release issuesSolo expertHoards knowledge instead of sharing — becomes a single point of failure and blocks team growthOverconfident designerProposes solutions without considering trade-offs — jumps to conclusions, resists alternative approachesRubber-stamperProduces AI-generated output without verifying it against the codebase, tests, or business contextInterview ProcessOur 5-round process is designed to evaluate you across all competency areas. AI tools are permitted in technical rounds.RoundFormatWhat We Evaluate1 — Hiring Manager Screen60 min, conversationalCareer trajectory, mentorship philosophy, technical influence examples, communication style2 — Take-Home + PR Discussion72h take-home + 60 min liveNavigating unfamiliar code, ownership and decomposition discipline visible in your PR, root-cause judgment, AI tool usage3 — System Design + Artifact Critique60 min, Miro boardRequirements gathering, schema/API design, trade-off articulation, calibrated code-review judgment on a teammate's PR4 — Team Interview (conditional)30 min, behavioralCollaboration patterns, mentorship behavior, negotiation behavior with cross-functional partners5 — Culture Add30 min, People TeamOrganizational values alignmentRound 4 is conditional: it runs when the team needs additional behavioral signal after Rounds 2 and 3, and is otherwise skipped. Your recruiter will tell you whether it's scheduled before your loop is finalized.The Round 2 (Take-Home + PR Discussion) and Round 3 (System Design) exercises are drawn from real problems so the technical evaluation is grounded in the work you'd actually be doing.What You’ll ReceiveCompetitive compensation including base salary, bonus, and equityEmployer-sponsored 401(k) with matchComprehensive medical, dental, and vision coverageFlexible time off and hybrid work environmentThe anticipated annual salary range for this role is $175,000 - $200,000. Actual compensation and title will be commensurate with experience, qualifications, knowledge, and skills.
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