[Hiring] Principal Applied AI Architect @Order.co

Role Description

We are hiring a Principal Applied AI Architect to set how data and intelligence work at Order.co: the target-state architecture, the standards that keep it coherent, and the company-level bets that turn proprietary procurement data into durable advantage. This is a senior individual contributor role. You will identify company-level objectives, make the business case to fund them, and land production systems that move primary company KPIs.

You will be the Head of Data's closest technical partner: the complementary technical leader to a strategy, product, and business lens. You keep those bets grounded in what we can actually do with the systems we have, and you are the person who knows what it would take to change that.

You sit on the data team. Applied AI Scientists take the architecture into product initiatives and own the science through to the metric. Senior AI / Data Engineers take the same architecture into the platform and own the production path. You are the person who holds those two paths on one spine, and who can still get on the keyboard when the first systems need to exist.

The work is architecture-first, with a real engineering bar. You will be fluent across stacks, treat security, reliability, and maintainability as delivery criteria rather than afterthoughts, and set a production quality standard that other teams can reuse. You will also stay a working applied scientist: statistical depth, model and agent judgment, and the ability to go from a strategic imperative to a shipped system. This is not an academic role. Understanding production systems and the business they serve is required, and you will get a change through operations and the other stakeholders who gate a real deploy.

Your job is to make that stack a company strategy, not a collection of projects. Accuracy funds the platform. The platform funds intelligence. Intelligence that cannot name the data it depends on is not a bet we take.

What you will own

• Company architecture for data and intelligence
• AI strategy, standards, and the investment case
• Delivery at company altitude

What we are working on now

• Accuracy at Scale.
• Adaptive Procurement.
• The intelligence layer on that spine.

Qualifications

• At least 14 years in applied data science, machine learning, data architecture, or production AI systems, with a track record of landing work that moved a company-level metric you can name.
• Experience as the technical counterpart to a product, strategy, or business leader, where your job was to ground the roadmap in what the systems could actually do.
• Deep working knowledge of production systems and of the business they serve.
• Ownership of target-state architecture across data and applied AI.
• Repeated delivery of production systems you personally designed, defended, and got through operational and stakeholder gates to production.
• The ability to size an initiative and turn that into a business case leadership actually funded.
• Real depth in current large language model and agent technology.
• Fluency across stacks and a production engineering bar.
• Heavy daily use of AI-native engineering workflows.
• Working implementation proficiency across at least two cloud or technical ecosystems.
• Evidence that you have mentored senior individual contributors and set standards other teams reused.

Preferred qualifications

• Experience with retrieval systems, vector search, ranking, recommendation, or production personalization.
• Experience designing source-of-truth models, semantic layers, or master and reference data.
• Experience setting model governance, monitoring, and responsible AI standards.
• Experience in e-commerce, B2B procurement, vendor management, financial products, or heavy integration with external systems.
• An advanced degree in a quantitative field is welcome; it is not a requirement.

What success looks like in the first 6 to 9 months

• The Head of Data is planning against a sequenced view of the data and AI portfolio that you own together.
• Target-state architecture and standards are in use.
• Applied AI Scientists and Senior AI / Data Engineers are working from the same spine.
• Evaluation, monitoring, and responsible-AI controls are the default on production AI.
• You have shipped something yourself, through the operational and stakeholder gates.

Working model

You sit on the data team as the Head of Data's closest technical partner, and you are hands-on from day one. You will partner with Product, Engineering, Operations, our Applied AI Scientists, and our Senior AI / Data Engineers. We ship iteratively and we judge work by the company outcome it produces. This role is remote within the United States.

Interview process

The process includes a conversation with the hiring manager, a live working session with platform and applied AI science, a conversation with an engineering leader, conversations with senior company and engineering leadership, and a values conversation with our People Ops team to close. That is typically six conversations. We do not usually include a take-home exercise.

Benefits

• Competitive compensation package
• Employer-sponsored 401(k) with match
• Comprehensive medical, dental, and vision coverage
• Flexible time off and hybrid work environment
• The anticipated annual salary range for this role is $225,000 - $275,000.