OverviewMicrosoft'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 business intelligence team builds and maintains Power BI which is the undisputed leader in BI tool in the industry today and serves as the bridge between data professionals & Office users. Power BI's core value proposition is to enable end users to get answers & insights from their data through data visualization.
The Power BI Core AI team is looking to hire a Senior Software Engineer, building AI-first capabilities that make enterprise data more accessible, governed, and useful to both human users and AI agents. You will design systems that bridge the gap between how data is stored and how it needs to be understood - transforming complex data assets into intelligent, programmatically consumable experiences. You will build Agentic AI experiences. As part of an agile team, you would work closely with engineers to deliver end-to-end solutions spanning web clients, cloud services, LLM-based agent integration, Benchmarking and Evals. Partnering with Applied Science, product management, and UX design, you'll have the opportunity to work across the full product stack and shape how AI transforms enterprise analytics at scale.
Responsibilities- AI-Native Development
- Independently uses appropriate artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC) in a disciplined manner. Takes responsibility for the content of their AI-generated requirements, design documents, code, and other assets, assisting other members of the team to do the same. Uses SDLC and engineering health measures (e.g., Accelerate, SPACE framework, Engineering System Success Playbook [ESSP]) to improve processes and practices, especially those involving AI. Experiments with AI tools and practices to improve their own capabilities.
- Write secure, performant, well-tested code across web clients and service-side components integrating with LLM-based agents; raise engineering standards through design reviews and thoughtful code reviews.
- Applies best practices to build code based on well-established methods and secure design principles while also applying best practices for new code development and formal validation of security invariants. Drives product development and scaling to customer requirements and applies best practices for meeting scaling needs and performance expectations and security promises.
- Reviews product code and test code to ensure it meets team standards, contains the correct test coverage, and is appropriate for the product or solution area. Brings insight to code reviews to help improve code quality, coaching and providing feedback to develop other engineers' skills. Conducts code reviews in a timely fashion that helps accelerate the pace of development on the team. Considers diagnosability, reliability, testability, and maintainability when reviewing code, and understands when code is ready to be shared or delivered. Applies and reviews for coding patterns, security risks, compliance issues, and best practices in code reviews, providing feedback on code to drive adherence to best practices. Uses automated source code analysis tools that are incorporated into the build/development process.
- Drives efforts to integrate logging and instrumentation for gathering telemetry data on system behavior such as performance, reliability, availability, usage, and safety mechanisms, and for allowing monitoring and investigating security-related concerns and scenarios for both live and A/B experiments for products, services, and offerings. Leverages telemetry feedback and effectiveness to independently improve subsequent monitoring designs.
- Identifies dependencies and incorporates them into the development of design documents for a product, application, service or platform. Actively identify other teams and technologies to leverage, how they interact, and where their own system or team can support others. Understands upstream and downstream interactions between systems and ensures security, compliance, performance, and reliability can be achieved across the entire stack. Collaborates with other teams to reach common goals where dependencies and validation concerns overlap. Works across teams to resolve conflicts around dependency ownership and required work.
Embody our culture and values
QualificationsRequired/Minimum Qualifications- Bachelor's Degree in Computer Science or related technical field 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.
Job Requirements: Other & Additional 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.
Preferred/Additional Qualifications- 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.
- Expertise building or operating large scale platforms and systems that support AI quality, safety, reliability, or experimentation with strong observability, diagnosability, and operational excellence for AI driven workloads.
- 1+ years of experience working with Large Language Models (LLMs) and Generative AI.
- Experience with distributed systems architecture, multi tenant cloud services, and high availability backend engineering.
- Ability to navigate ambiguity, deliver in an agile environment, adopt new technologies, and collaborate effectively across teams.
Software Engineering IC4 - The typical base pay range for this role across Canada is CAD $114,400.00 - CAD $203,900.00 per year.
Find additional pay information here:
https://careers.microsoft.com/v2/global/en/canada-pay-information.html
Software Engineering IC4 - L'échelle salariale de base typique pour ce rôle dans l'ensemble du Canada est de 114,400.00 $ CAD à 203,900.00 $ CAD par année.
Pour plus d'information au sujet de la rémunération, veuillez cliquer ici:
https://careers.microsoft.com/v2/global/en/canada-pay-information.html
Ce poste sera ouvert pendant au moins cinq jours et les candidatures seront acceptées de façon continue jusqu'à ce que le poste soit pourvu.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
