Senior Data & AI Platform Engineer

Orchestry is a rapidly growing SaaS company in the Microsoft 365 ecosystem, helping organizations simplify, govern, and automate their digital workplace. We work globally with partners and enterprise customers and operate as a fully remote company by design. 

As we scale, we are intentionally building the foundation for the future of the company including our people, leadership capability, and culture. This role is critical to ensuring Orchestry grows with focus, agility, and strong execution. 

We help organizations adopt, govern and manage Microsoft 365 with beautiful, compelling and innovative software. Our Orchestry tool is a leading platform that manages over 500,000 Microsoft teams each month across multiple customers, geographies and verticals. 

Orchestry isn't just a run-of-the-mill Microsoft partner that is creating a product on the side. We are 100% a product-led organization that values innovation and best practices from inside and outside of Microsoft to create great software. We have long-lasting relationships with partners and customers. We are fearless and innovative. We believe that there is too much poor, un-intuitive software built for Microsoft 365 administrators and users. Our goal is to change that.   

We only hire and want to work with the best in the world. Our team is composed of Microsoft MVPs, founders of successful startups and those with a burning desire to make a difference. Headquartered in Canada we don't care who you are or where you live. If you want to build a great career and work with the best then get in touch.   

Are you the kind of data engineer who sees a warehouse and thinks “this should power decisions and automation, not just dashboards”? Have you built production-grade AI systems that actually reason over real company data instead of toy examples? If so, this role is for you.
Orchestry is hiring a Senior Data & AI Platform Engineer to own and evolve our Microsoft Fabric–based Data Warehouse and turn it into the foundation for secure, agentic AI workflows across the company.
This is a platform ownership role. The Fabric warehouse isn’t just for reporting, it’s the backbone for reliable, governed data, AI-accessible context, and intelligent internal automation. You’ll sit at the intersection of Data Engineering and Applied AI, building the infrastructure and agentic systems that help every department make better decisions. This is not a BI dashboard role and not an experimental AI sandbox. Success comes from production-level thinking, strong software instincts, and the ability to build systems that scale responsibly across the business.

• Own and evolve Orchestry’s Fabric-based Data Warehouse as the trusted foundation for analytics and AI.
• Design and implement scalable data models, transformations, and refresh strategies
• Establish data quality checks, lineage, and trust signals
• Partner with Engineering and Product to onboard new data sources
• Define warehouse patterns that are reliable, understandable, and AI-consumable
• Monitor and optimize Fabric capacity usage, storage growth, refresh schedules, and query performance
• Ensure the data platform scales sustainably as adoption increases

You become the steward of analytical truth inside the company.

• Design the warehouse not just for reporting, but for reasoning.
• Create schemas and semantic layers optimized for retrieval, aggregation, and temporal analysis
• Build curated datasets and feature-like abstractions for AI consumption
• Develop secure, scalable retrieval pipelines (RAG-style patterns) across structured and unstructured data
• Ensure governed access paths so AI agents don’t query raw, unstructured chaos
• Embed lineage, trust signals, and validation checks into downstream AI workflows

You’ll build the bridge between analytics and AI.

• Develop internal AI agents that query the warehouse, interpret results, and recommend or take action
• Create automation workflows across
  • Usage analysis
  • Customer insights
  • Sales enablement
  • Support intelligence
  • Engineering and product signal
• Build reusable frameworks for internal agents, including tool orchestration, prompt management, and workflow execution
  
• Integrate AI systems with internal platforms to enable automated actions and intelligent recommendations
  
• Develop evaluation approaches to measure agent accuracy, reliability, and business impact

• Design and build customer-facing AI agents that reason over customer environment data and take actions using Orchestry’s product capabilities through defined tool interfaces
  
• Define tool schemas, action boundaries, and safety guardrails for autonomous agent execution, including tenant data isolation and blast radius constraints
  
• Own the LLM orchestration layer managing tool selection, prompt construction, context optimization, and response quality for production use
  
• Ensure customer-facing agents operate securely, predictably, and in alignment with governance controls
  

The warehouse answers what happened. Agents answer what should we do about it.

• Define and enforce role-based access controls and data boundaries
• Ensure AI systems respect data sensitivity, compliance, and auditability
  
• Implement guardrails so AI adoption increases trust instead of creating shadow chaos
• Document systems, processes, and architectural decisions for long-term maintainability

• 6+ years experience in software engineering, data engineering, applied AI engineering, or a related technical role
• Proven experience building production-grade AI systems beyond proof-of-concepts
  
• Strong hands-on experience with LLMs, agentic workflows, and tool-using systems
• Experience integrating AI systems with structured and unstructured data sources
• Demonstrated ability to design AI-ready data models and retrieval patterns for reasoning and automation
• Experience with modern data warehouses or analytics platforms
• Strong software engineering fundamentals (APIs, testing, version control, maintainable architecture)
• Ability to independently own ambiguous problems and deliver end-to-end solutions
• Strong communication skills with both technical and non-technical stakeholders 
• Experience building AI-powered features shipped as part of a customer-facing product, not just internal tooling
• Experience designing tool/function-calling interfaces for LLMs and working with multi-tenant data architectures

• Experience with Microsoft Fabric, Azure, or Microsoft-centric data ecosystems
• Experience managing warehouse cost optimization and compute efficiency
  
• Familiarity with enterprise governance, access controls, and SOC 2–aligned environments
• Experience building internal tools used by non-technical stakeholders
• Deep curiosity about emerging AI agent frameworks and enterprise AI tooling

• A chance to build and shape the people function at a pivotal growth stage 
• Fully remote environment built intentionally for trust and outcomes 
• Competitive salary and stock options 
• Extended health benefits package 
• Real ownership, real impact, and an opportunity to help define the future of the company