Principal Software Engineer

Microsoft bets on Artificial Intelligence (AI) as the next growth opportunity for the company. OpenAI, Mistral, and other Large language Model (LLM) driven innovations are happening throughout the industry. Azure AI is focused on building a platform that makes it easy for both first party Microsoft teams and third-party customers to build cutting edge applications on top of these large language models.

The Back Plane team in Azure Machine Learning is looking for a Principal software engineer who loves to build scalable, highly available, and secure microservices that run in Kubernetes. The infrastructure team focuses on managing a large fleet of Azure Kubernetes Services (AKS) that represents the control plane for AzureML.

The team focuses on:

• Managing Kubernetes Cluster Deployments at Scale
• Secure Control Plane / Data Plane assets from malicious attacks and unauthorized access using industry standard tools and frameworks
• Automate Monitors and critical alerts using best in class observability tools such as: Azure Monitor, Prometheus, Azure Data Explorer, Grafana
• Automate CI/CD deployments using YAML builds and release

For the Azure ML platform, we build tools to increase the observability of the applications running in the Kubernetes clusters, improve the speed, security, and reliability of our deployments, secure our supply chain and services, and debug production with ease. We use the best of open source, like Prometheus, Grafana, and NGINX, and build solutions to enable Azure ML to deliver a global service that handles large scale ML training and inferencing workloads

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical discipline, AND 15+ years of technical engineering experience with coding in languages including, but not limited to, C#, TypeScript, JavaScript, React, or Python, OR equivalent experience
• 10+ years of experience with coding in one of C#, Python, Go, Rust, Java, C or C++
• Experience with improving service operations, SLA/SLOs or engineering fundamentals
• Deep experience using Kubernetes in building large scale cloud services, or distributed systems
• Deep experience in Observability pipelines, Open Telemetry, frameworks, Microservices architecture, K8s, NGINX/Istio Ingress, Observability (Logs, Metrics, etc..), SLA Automations, Network Layer protocols is a plus
• Experience in defining and releasing product KPIs, distributed tracing, resource optimization, and working through security and privacy challenges
• Excellent communication, collaboration skills, team player, thrive to make a difference

Preferred Qualifications:

• Hands-on experience with building AI, ML related products or platforms
• Experience running engineering teams focused on building delightful, resilient services

#IDCAIPlatformHiring

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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.

As a Software Engineer on our team, you will drive the design, development, and support of the platform that powers Azure Machine Learning. You’ll work across teams to help make the whole organization successful. Your responsibilities will include the following:

• Investigate live site issues and implement and deploy fixes
• Participate in an on-call rotation
• Drive quality engineering via code reviews and design discussions
• Build, develop and grow a healthy, diverse, and agile engineering team
• Foster a culture of high-performance, inclusion and manager excellence
• Set the strategy and KPIs and OKRs for the team to create clarity, generate energy and deliver success
• Promote the adoption of good engineering principles, coding standards and patterns to build robust and maintainable architecture and designs
• Collaborate with cross-disciplinary partners, engineering leaders and stakeholders to build innovative solutions that delight our customers
• Lead by example, using the product, raising the quality bar, and improving the team's response to customer incidents and feedback
• Demonstrate drive for results and a passion for continuous learning

Good story telling for team WINS that could provide clear value proposition as a platform team.