AI Engineer II & Senior AI Engineer - Getting Customers Ready for AI

Microsoft•Redmond, WA

About The Position

Microsoft Security's Getting Customers Ready for AI team is seeking an AI Engineer II and a Senior AI Engineer to help design, build, and deploy AI-native systems that enable customers to securely adopt AI at enterprise scale. This role sits at the intersection of AI engineering, security, and real-world application, where you will develop intelligent systems that transform signals across identity, devices, data, applications, and infrastructure into actionable insights, automation, and customer value. You will work across the AI lifecycle—from model development and data pipelines to production deployment, monitoring, and continuous improvement—while helping shape secure and scalable AI solutions for enterprise environments. Working in a collaborative environment, you will partner with engineering, data science, product, and customer-facing teams to bridge the gap between AI innovation and real-world applications, enabling automation, enhanced decision-making, reasoning, and innovation. 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.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Experience building, deploying, or contributing to AI/ML systems, including machine learning models, LLM-based applications, RAG architectures, agentic workflows, or other data-driven solutions.
Demonstrated programming skills in Python or similar languages for AI development, data processing, system integration, and automation.
Knowledge of machine learning fundamentals, statistics, optimization, and data processing techniques.
Experience developing and operating scalable data pipelines, distributed systems, or cloud-based AI/ML workloads.
Familiarity with MLOps practices such as CI/CD, model deployment, monitoring, versioning, containerization, and AI lifecycle management.
Experience working with modern AI technologies, including LLMs, vector databases, retrieval systems, and related AI frameworks and tools.
Problem-solving skills, curiosity, and the ability to learn quickly, navigate ambiguity, and deliver solutions in rapidly evolving technology environments.

Responsibilities

Design, build, and improve AI-powered solutions, including machine learning models, LLM-based applications, RAG systems, and agentic workflows that solve customer and business challenges.
Develop and operate scalable data pipelines, ETL processes, training datasets, and AI infrastructure to support model development, deployment, and lifecycle management.
Deploy, monitor, and optimize AI systems using MLOps practices, leveraging telemetry and feedback to improve performance, reliability, security, and scalability.
Transform large-scale, multi-source data into contextual intelligence, automation, and decision-support capabilities that drive customer and business outcomes.
Build and integrate AI capabilities into applications, services, APIs, and platforms to deliver end-to-end customer experiences.
Contribute to AI readiness initiatives through frameworks, metrics, telemetry, and solutions that help customers securely adopt and operationalize AI technologies.
Demonstrate a builder mindset by rapidly prototyping, experimenting, and iterating on AI solutions while navigating ambiguity and evolving requirements.
Partner across engineering, data science, product, and customer teams to translate complex problems into practical, AI-driven solutions.
Write maintainable, well-tested code and contribute to engineering excellence through documentation, operational rigor, governance, and adherence to security, compliance, and Responsible AI practices.
Embody our culture and values.