Shape the future of AI with Microsoft CoreAI and the Azure AI Foundry Customization team. Empower AI applications globally by building cutting-edge platforms that drive innovation across Azure and Microsoft's flagship products. This role offers end-to-end ownership, from high-level APIs to granular controls, focusing on making frontier AI models accessible, efficient, and cost-effective for enterprises.

Contribute to pre-training, mid-training, and post-training solutions, enabling AI systems that continuously learn and adapt. You will deliver services, pipelines, ML recipes, evaluations, and integrations, leveraging Azure's world-class infrastructure and GPU capabilities. Join us to make agentic AI economically viable for every enterprise and showcase your work at industry events like Microsoft Build and Ignite.

Collaborate with data scientists and developers to create abstractions, infrastructure, and features for training, testing, scaling, and optimizing machine learning algorithms. Drive customer-inspired innovations into software with holistic ownership of features.

Key responsibilities include: - Independently utilize AI agents, skills, and practices throughout the software development lifecycle. - Understand customer/user requirements and translate them into features. - Develop and execute clear test strategies to ensure solution quality and build testable code. - Create extensible and maintainable product feature code, minimizing defects. - Review product feature code, ensuring correct test coverage and adherence to team standards. - Implement debugging tools, tests, logs, and telemetry for verification. - Strive for automation in production deployment, aiming for zero-touch operations. - Apply security best practices for hardening product features.

Requires a Bachelor's or Master's degree in Computer Science or a related technical field, combined with 4+ years of technical engineering experience. Proficiency in coding languages such as C#, Java, or Python is essential, or equivalent practical experience.

Experience with day-to-day AI agents and tool usage is necessary. Familiarity with AI/ML internals is highly advantageous. Proven ability to write production code for internet-scale services and distributed systems is expected.

Candidates must possess strong debugging skills, the ability to read and work with large codebases, and excellent communication and presentation abilities. Engineering knowledge of machine learning systems and data pipelines is a plus. Collaboration and teamwork are key, along with the ability to meet security screening requirements. This role involves 3 days per week in-office work in Bangalore, India.