Transform enterprise data and systems with modern, AI-enabled capabilities as a seasoned AI/ML Engineer at S&P Global. This role fosters collaboration with business partners, data stakeholders, and product teams to deliver measurable business outcomes.

You will design, develop, deploy, and maintain AI/ML solutions using cloud-native AWS architectures. This involves applying advanced techniques across the entire AI/ML lifecycle, from data engineering and model development to deployment and production support. Your expertise in applied machine learning, Generative AI, and Large Language Models will be crucial for integrating AI capabilities into production systems.

Join a team leveraging modern engineering platforms like GitHub, TeamCity, and AWS, alongside AI-assisted tools such as GitHub Copilot, to enhance developer productivity. We embrace fast-paced environments and modern engineering practices to ensure code quality, model governance, scalability, and efficient delivery.

Design, implement, and optimize machine learning models and AI applications to address complex business challenges.

Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to create innovative solutions.

Develop and deploy AI/ML solutions on AWS using cloud-native architectures and services like Bedrock, SageMaker, and Lambda.

Apply expertise in Generative AI, LLMs, and RAG architectures, including practical experience with vector databases and prompt engineering.

Ensure secure and responsible AI development, focusing on data privacy, explainability, and adherence to enterprise standards.

Contribute to CI/CD pipelines, containerization with Docker, and Infrastructure as Code practices.

Effectively translate business problems into technical AI/ML solutions and communicate findings to both technical and non-technical audiences.

Possess a Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field.

Demonstrate 10+ years of overall software development experience, with at least 3 years focused on hands-on machine learning or AI application development, evidenced by a track record of delivering production-ready solutions.

Exhibit strong Python programming skills, including experience with API development using FastAPI or Flask. Backend development experience in C# or Java is a plus.

Showcase solid experience developing AI solutions within the AWS ecosystem, utilizing services such as Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3.

Apply practical knowledge of Large Language Models and Generative AI frameworks like LangChain or LlamaIndex, including in-depth understanding of RAG systems and their components.

Familiarity with vector databases (e.g., Pinecone, FAISS, OpenSearch), text embeddings, and prompt engineering is advantageous.

Understand cloud security fundamentals, including OAuth 2.0 authentication, IAM policies, secure API design, and data protection.

Experience with DevOps tools and practices, such as CI/CD, Docker, and IaC (CloudFormation, AWS CDK, Terraform), is required.

Proficiency in SQL and data modeling, coupled with a strong grasp of machine learning algorithms, deep learning architectures, and data science tools for preprocessing and feature engineering.

Utilize AI-assisted engineering tools like GitHub Copilot to boost productivity and ensure code quality and responsible AI practices.

Possess excellent analytical, problem-solving, and communication skills, with the ability to thrive in agile, team-oriented environments.