Description:
This role is a unique opportunity for hands-on architects and platform engineers to grow into the next step in their career journey.
- 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 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.
- 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. Provide guidance and mentorship to junior engineers, fostering their professional growth and development.
- 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, and adherence to model and data governance standards
Compensation/Benefits Information: (This section is only applicable to US candidates)
S&P Global states that the anticipated base salary range for this position is $125,000 to $220,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications.
In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.
This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.
What We’re Looking For:
Basic Required Qualifications:
- 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 (with some previous experience with front-end technologies such as React, Vue or Angular JS) and APIs at speed and scale, including integration with enterprise applications and APIs.
- Experience with MLOps tools/frameworks (e.g. 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.