Principal Software Engineer

Security represents the most critical priority 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 aim to reshape security and empower every user, customer, and developer with a security cloud that protects them through end-to-end, simplified solutions.

The Microsoft Security organization accelerates Microsoft’s mission to secure digital technology platforms, devices, and clouds in our customers’ heterogeneous environments while safeguarding our internal estate. Our culture emphasizes a growth mindset, inspiring excellence, and encouraging teams and leaders to bring their best daily. This enables us to create life-changing innovations that impact billions of lives worldwide.

The SCIP (Sovereign Compliance and Infrastructure Platform) team provides leadership, direction, and accountability for Data Platform and Engineering, Security Researchers tools and platforms, Developers productivity platforms, Hyper scalable infrastructure, and other Industry standard security and compliance regulations.

 

The team proudly develop and maintains highly scalable big data engineering platforms (synthesizing Petabytes of data) and providing deep product and engineering data insights to Senior leadership. As we are stepping into advance stage of Data Engineering and Science, we are looking for a Principal Software Engineer to help us design, architect and build large scale data platforms. The position involves developing and integrating machine learning models, creating self-service reporting platforms for stakeholders, Integration of AI and delivering data-driven insights to solve complex business problems. It also includes defining metrics to evaluate model performance and ensuring that solutions align with business goals, scale effectively, and meet quality standards.

We are a diverse and inclusive workplace and strongly encourage to bring true self to the work. We believe diversity enhances innovation and strengthens teams, enabling us to better serve our global customer base.

Required:

• Deep expertise in Python, SQL, Databricks, Azure ML, Spark, and experience with large language models (LLMs), supervised/unsupervised learning, and natural language processing (NLP). 
• Experience in architecting and integrating machine learning models into customer-facing products, with a focus on optimizing relevance, personalization, and user engagement. 
• Data science modeling, statistics, analytics, business intelligence or data-driven business strategy. 
• Strong analytical, problem-solving, and organizational skills.
• Proven ability to deliver Greenfield projects from ideation to production.
• Demonstrated ability to influence without authority and drive cross-functional collaboration.
• Excellent communication and interpersonal skills to engage effectively with diverse stakeholders.

Preferred:

• Hands-on experience with Azure Cloud and multi-cloud development/deployment.
• Expertise in platform development for productivity and research teams.
• Deep understanding of large-scale data architectures, machine learning pipelines, and distributed systems.
• Strong ability to technically evaluate and architect solutions for complex problems.

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.

• Design and develop large-scale distributed data engineering solutions and services with a focus on performance, reliability, and scalability. Also, expected to drive projects from concept to production, including design reviews, coding, testing, deployment, and monitoring.

•  Technically mentor junior and mid-career engineers while fostering collaboration across diverse teams.

• Machine Learning Innovation: Lead the development of advanced machine learning models that address key business challenges. Use LLMs and other data to create solutions for business insights. Generalizes machine learning (ML) solutions into repeatable frameworks (e.g., modules, packages, general-purpose software) for others to use. Develops operational models that run at scale. Partners with others to identify and explore opportunities for the application of ML and predictive analysis.
• Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics. Develops deep expertise in specialized areas by staying abreast of current and emerging methodologies in AI and ML.
• Relevance & Personalization Models: Architect and refine both supervised and unsupervised models that optimize the relevance of key product features. Improve security product experiences by extracting meaningful signals from data and telemetry. 
• Collaborate on Product Development: Partner closely with product and engineering teams to translate user needs into actionable machine learning solutions. 
• Utilize Industry-Leading Tools: Access Microsoft Security’s vast data scale, computing resources, and advanced machine learning frameworks to deliver high-impact solutions. Apply prompt optimization, fine-tuning, and retrieval-augmented generation (RAG) techniques to ensure models deliver optimal results. 
• Performance Metrics: Define, track, and refine key performance metrics for machine learning models. Continuously iterate on models based on user feedback and real-time data to improve accuracy, precision, and recall.