Senior Software Engineer
About The Position
Microsoft's Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. Within Azure Data, the big data analytics team provides a range of products that enable data engineers and data scientists to extract intelligence from all data – structured, semi-structured, and unstructured. We build the Data Engineering, Data Science, and Data Integration pillars of Microsoft Fabric. The Fabric Data Engineering Experience & Infrastructure team is hiring an AI Engineer to help build LLM-powered data engineering experiences and infrastructure for Fabric Data Engineering, based on Apache Spark. You will help implement agentic workflows and scalable LLM-backed data features (e.g., AI Functions integration, notebook copilots, evaluation/telemetry etc) with advanced capabilities designed to help Data Engineers achieve more through Microsoft Fabric. We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.
Requirements
- Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
- 4+ years experience in Frontend + UX engineering skills: React + TypeScript, accessibility, performance, and building user-centered flows.
- 4+ years experience in Backend / full-stack fundamentals: service/API design, debugging distributed systems, reliability/operability, and production ownership.
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Nice To Haves
- Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
- Experience building and operating cloud services (Azure preferred), including telemetry, monitoring, experimentation/rollout strategies, and cost/latency awareness.
- Experience with data engineering concepts and systems (e.g., Spark, notebooks, lakehouse-style workflows) and the needs of professional data engineers.
- Understanding of modern AI/LLM-assisted product patterns (tool use, grounding, evaluation mindset, trust/safety guardrails) and how to ship these experiences.
- Ability to collaborate across disciplines (PM, Design, Research, partner engineering teams) and drive ambiguous problems to crisp execution.
Responsibilities
- Design, build, and ship scalable backend services and/or libraries in Python that power Fabric Data Engineering and Data Science experiences
- Develop LLM-enabled capabilities (prompting patterns, tool/function calling, RAG/grounding, orchestration/agents) with strong attention to latency, reliability, and cost
- Build robust data pipelines and distributed compute solutions (Spark/PySpark) to support model/data workflows, feature generation, and large-scale analytics
- Define evaluation strategies for LLM features (offline/online metrics, quality gates, safety checks), and implement telemetry/monitoring to continuously improve quality
- Apply Responsible AI and security/privacy best practices (data handling, governance, access controls) when integrating AI into customer-facing products
- Collaborate with PMs and partner engineering teams to translate scenarios into clear technical designs and incremental deliverables
- Maintain and operate services in production, participate in on-call/incident response, and drive improvements in operational excellence
- Review code and designs, mentor peers through constructive feedback, and contribute to engineering best practices across the team
Benefits
- The typical base pay range for this role across Canada is CAD $114,400 - CAD $203,900 per year.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
