Senior AI / Data Engineer

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. As 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, partnering closely with various teams to deliver reliable data systems and high-quality datasets.

Responsibilities:

• Design, build, and maintain scalable data pipelines, integrations, and AI workflows
• Develop reliable and maintainable ETL/ELT systems that support analytics, operational reporting, and AI-driven products
• Contribute to the architecture and evolution of the company’s data platform and AI infrastructure
• Build systems and services with a focus on simplicity, iterative development, reliability, and long-term maintainability
• Continuously optimize data architecture to support evolving business and product requirements
• Partner with stakeholders to translate business problems into scalable data and AI solutions
• Develop infrastructure automation and deployment workflows to improve engineering velocity and operational consistency
• Implement infrastructure as code (IaC) practices using tools such as Terraform or CloudFormation
• Build and maintain CI/CD pipelines and automated testing workflows
• Develop monitoring, alerting, and observability solutions for data and AI systems
• Improve reliability, scalability, and operational efficiency through automation and proactive system improvements
• Participate in incident response and operational support rotations as needed
• Contribute to production-ready AI systems and workflows where they provide measurable business value
• Evaluate and integrate AI-assisted engineering tools responsibly and pragmatically
• Support the deployment and operationalization of machine learning and AI-powered services
• Help establish best practices for AI-assisted software development, evaluation, and operational safety
• Contribute to roadmap planning, technical design discussions, and engineering prioritization
• Mentor junior and mid-level engineers through code reviews, pairing, and technical guidance
• Collaborate cross-functionally with Engineering, Product, Analytics, and Operations teams
• Communicate technical trade-offs, implementation details, and operational risks clearly to stakeholders
• Promote engineering best practices around testing, observability, documentation, and operational excellence

Requirements:

• You are motivated by accountability and ownership of outcomes
• You are results-oriented and focused on delivering reliable, working systems
• Writing tests is an integral part of your development process
• You know how to design and build software incrementally
• You enjoy collaborating with others to solve complex technical problems
• You are collaborative, open-minded, and continuously improving your craft
• You are curious and pragmatic about AI-driven solutions and apply them thoughtfully where they create real value
• You understand both the strengths and limitations of AI-assisted engineering tools and evaluate their output critically
• Strong proficiency in Python and SQL
• Hands-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 SQS
• Experience implementing infrastructure as code using Terraform or similar tooling
• Strong experience designing event-driven, serverless architectures using AWS Lambda, API Gateway, EventBridge, and SQS/SNS
• Hands-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 Formation
• Hands-on experience with cloud data warehouses (preferably Snowflake) including schema design, performance tuning, cost optimization, and access control
• Experience designing and maintaining reliable ETL/ELT pipelines and distributed data workflows
• Hands-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 CircleCI
• Understanding of observability, monitoring, and operational best practices for data systems
• Strong understanding of data security, access controls, and protecting sensitive data
• Experience building automation and operational tooling using Python or similar languages
• Familiarity with production AI/ML workflows and operational considerations for AI-enabled systems
• Experience using AI-assisted engineering tools (e.g., Claude Code, Codex, GitHub Copilot) responsibly to improve productivity and engineering quality