Associate Director of Generative AI Platform Engineering

6 days ago

Toronto, Ontario, Canada S&P Global Full time
About the Role

We are seeking an experienced Associate Director of Generative AI Platform Engineering to join our team at S&P Global. This role will be a critical part of leading our AI-driven transformation to drive value both internally and externally for our customers.

Responsibilities and Impact
  • Lead the design, development, and deployment of a generative AI platform, ensuring optimal integration with enterprise systems and standards.
  • Act as a hands-on developer and architect, creating a robust and scalable solution tailored to support AI-driven applications.
  • Demonstrate technical leadership and hands-on expertise in generative AI technologies and cloud architecture.
  • Responsible for the full stack development of the platform for AI products, including custom architecture for batch and stream processing-based AI ML pipelines.
  • Ensure the deployment and management of scalable and reliable platform and application infrastructure for AI, ML, GenAI, LLM products.
  • Lead the development, integration, and testing of scalable APIs.
  • Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health.
  • Identify and implement optimizations to improve system efficiency.
  • Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
  • Collaborate closely with ML teams, business, and PM stakeholders in full-stack implementation efforts and ensure technical milestones align with business requirements.
  • Implement security measures and compliance standards of the platform and APIs to ensure adherence to industry regulations.
  • Mentor technical engineering talent and provide guidance and mentorship to junior engineers.
  • Maintain documentation and architecture blueprints that guide the platform strategy and operational runbooks.
  • Ensure the use of standards, governance, and best practices in ML pipeline and ML model monitoring.
What We're Looking For
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Deep understanding of platform development and deployment at the scale of large enterprises.
  • Strong distributed systems skills and knowledge, strong system architecture skills.
  • 7+ years of hands-on cloud platform engineering experience, preferably with AI/ML development experience.
  • Significant hands-on development experience in integrating, evaluating, deploying, operationalizing scalable full-stack and web-application solutions, including integration with enterprise applications and APIs.
  • Experience with MLOps tools/frameworks, such as MLflow or similar.
  • Strong knowledge and deep experience of Python, proficiency in multiple programming languages and frameworks relevant to cloud development, such as Kubernetes, Serverless, and cloud PaaS offerings.
  • Experience and knowledge of foundational Generative AI principles, such as prompt engineering, RAG, finetuning, etc.
Benefits

We take care of you, so you can take care of business. We care about our people. That's why we provide everything you—and your career—need to thrive at S&P Global.

  • Health & Wellness: Health care coverage designed for the mind and body.
  • Flexible Downtime: Generous time off helps keep you energized for your time on.
  • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
  • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
  • Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in-class benefits for families.
  • Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

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