Principal Software Architect

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.

Copilot for Security, the first security focused generative AI product, is at the forefront of Microsoft’s AI revolution and reimagines how security gets done and how we do security. It empowers security and IT teams to protect at the speed and scale of AI making them more productive and skilled. Copilot for Security is also an AI platform, tailored to the security space, that enables GAI capabilities to be integrated in the existing 1st party and 3rd party security products and services. As pioneers in the field, we are committed to addressing the evolving challenges and opportunities within the realm of cybersecurity and continue to be the market leaders when it comes to GAI and Security.

We are seeking an accomplished Principal Software Architect with deep domain expertise in Security, AI technology and distributed systems to partner with the chief architect to evolve the platform to support the rapid pace of technological advancement in the AI space. In this pivotal role, you will be instrumental architecting the AI production services to meet and exceed our customers’ (developers and researchers) requirements. You will collaborate closely with engineering leaders across various teams to define our architecture vision of scalable ML-driven systems, chart a strategic path, and ensure that our services are robust and resilient for large enterprise customers. The ideal candidate will have deep experience in both software architecture and machine learning, capable of bridging the gap between data science and engineering to build robust, efficient, and scalable systems. You will play a key role in designing end-to-end ML pipelines, ensuring system scalability, reliability, and integration with other business-critical systems.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required:

• Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Experience in ML architecture and engineering and ML lifecycle and pipelines, along with experience leading large-scale initiatives in a complex, fast-paced environment.
• Proven experience in architecting and deploying ML models in production environment

Other Requirements:

• 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:

• Experience with Retrieval-Augmented Generation (RAG) architectures and AI model management.
• Knowledge of security and compliance frameworks in ML-driven environments.
• Prior experience leading AI/ML initiatives in an enterprise setting.
• Experience with cloud infrastructure automation tools and techniques.
• Experience working with AI/Machine Learning services and platforms.
• Familiarity with Microsoft Azure’s security and compliance frameworks.
• Exceptional communication and collaboration skills, with the ability to influence and drive cross-functional initiatives.

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $180,400 - $294,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:  https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until October 22, 2024.

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.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.

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• Lead the architectural design and development of end-to-end ML solutions.
• Collaborate with data scientists, ML engineers, software engineers, and product teams to transform ML models into production-grade solutions.
• Design scalable, high-performance ML pipelines for real-time and batch processing, ensuring alignment with business objectives.
• Define architectural best practices for ML-driven applications, including data pipelines, model deployment, and monitoring.
• Evaluate and integrate ML frameworks, libraries, and technologies to ensure efficient implementation.
• Oversee the governance, compliance, and security aspects of the ML architecture.
• Optimize and automate model training, deployment, and monitoring in collaboration with the engineering teams.
• Ensure that ML systems are built with fault tolerance, performance, and observability in mind.
• Work closely with stakeholders to align technical strategy with business needs.
• Stay up to date on the latest trends in machine learning, AI, and software architecture.