About the Role:

Grade Level (for internal use):

Job Title: Full-Stack Engineer - Associate Director

The Data Science COE at S&P Global is looking for a hands-on Full-Stack Engineering leader  to lead the full-stack engineering design and development efforts for the ML applications developed by the COE. role will lead, implement and define the full-stack platform strategy, and design and develop front-end and application layer solutions for our ML services while working with a broad range of partners across data, technology and business teams.

In this role, you will play a pivotal role in leading and implementing the design, test, and implementation of various software applications for our Machine Learning solutions. You will create software, applications, and scalable web services, while also providing leadership for software platform and engineering teams

You will be instrumental in developing full-stack solutions for our ML products and prototypes in a world class AI ML team while working alongside well-known experts and researchers in AI ML modeling, ML engineers and data science and data engineering teams. You will be a critical part of leading S&P’s AI-driven transformation to drive value internally and for our customers. 

S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for a hands-on full-stack engineer and application developer to grow into the next step in their career journey and apply her or his domain expertise for leading the integration of  front-end applications and APIs for deep learning, GenAI, and LLM back-end models to drive business value for multiple stakeholders. The ideal candidate must have deep design and hands-on scalable web application  development expertise, and integrating data-driven solutions with business functions to create the next generation of AI-powered capabilities.

Responsibilities include:

• Full-Stack  System Architecture Design : Develop scalable full-stack system and front-end applications for ML back-end 

• Full-stack UI and System Development for AI products: Responsible for the development of custom architecture for batch and stream processing-based AI ML pipelines including data ingestion to preprocessing to scaled AI model compute and ensure the architecture meets all SLA requirements. Work closely with members of technology and business teams in the design, development, and implementation of Enterprise AI platform
   
• System Infrastructure Management: Ensure the deployment, and management of scalable and reliable system and application infrastructure for AI, ML , GenAI, LLM products.

• API development, integration and Testing: Lead the development and integration of scalable APIs .

• Monitoring and Optimization: Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health. Identify and implement optimizations to improve system efficiency.

• Internal Collaboration: Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.

• Stakeholder Engagement and Collaboration: Collaborate closely with ML teams, business and PM stakeholders in full-stack implementation efforts and ensure technical milestones align with business requirements.

• Security and Compliance: Implement security measures and compliance standards of the full-stack systems and APIs to ensure adherence to industry regulations.

• Mentorship: Mentor technical engineering talent. Provide guidance and mentorship to junior engineers, fostering their professional growth and development.

• Documentation: Maintain comprehensive documentation of full-stack systems and applications for reference and knowledge sharing.

• Standards and Best Practices: Ensure the use of standards, governance and best practices in ML pipeline monitoring and ML model monitoring, and adherence to model and data governance standards

• Problem Solving: Troubleshoot complex issues related to full-stack system deployments and develop innovative solutions.
  
   

REQUIRED SKILLS/QUALIFICATIONS

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 
   
• Experienced professional (7+ years experience) as full-stack engineer, architect, engineer with core hands-on experience
   
• 4+ years hands-on experience in integrating, evaluating, deploying, operationalizing scalable full-stack and web-application solutions and APIs at speed and scale, including integration with enterprise applications and APIs

• 5+