Lead AI/ML Engineer

Role Overview

• Architect and deliver production-grade autonomous AI workflows that go well beyond conversational assistants.
• Lead hands-on engineering of stateful agentic applications using agent orchestration frameworks capable of coordinating multiple autonomous components.
• Define and implement robust communication patterns that allow agents to delegate sub-tasks, negotiate execution paths, and coordinate outcomes in dynamic environments.
• Engineer control flows for non-deterministic systems, including message passing, persistent memory, recoverability, and interruptible execution for long-running tasks.
• Establish universal interfaces between agents, enterprise data sources, and operational tools to ensure modularity, reusability, and consistent governance.
• Build routing and fallback strategies across multiple model endpoints; optimize context management, latency, and inference cost while maintaining reliability.
• Package and deploy workloads via containerization and cluster orchestration, using cloud-native services for scaling, isolation, and secure runtime operations.
• Develop and maintain high-throughput ingestion and transformation pipelines that convert raw operational signals into structured, machine-consumable context.
• Ensure agents can access near-real-time operational data by designing efficient retrieval patterns and optimizing vector databases and associated retrieval architectures.
• Serve as the technical bridge between AI and data teams—translating agent needs into schemas, data contracts, SLAs, and pipeline specifications, while resolving bottlenecks hands-on.

Requirements

• 7+ years in software engineering, data engineering, and/or machine learning engineering, with demonstrated ownership of production systems.
• 2+ years building and deploying LLM-based applications and/or agentic systems in real-world environments.
• Proven experience designing AI-ready storage layers across vector databases, relational and NoSQL databases, and modern lakehouse/warehouse architectures.
• Strong capability deploying and scaling services on major cloud platforms using containerization, cluster orchestration, CI/CD, and secure runtime practices.
• Strong grasp of retrieval-augmented generation, embeddings, context strategies, prompt/system design, and failure modes in deployed systems.
• Ability to blend ML intuition (model behavior, uncertainty, evaluation) with software excellence (APIs, async systems, reliability engineering).
• Advanced proficiency in Python for building modular, testable, maintainable production services.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field (or equivalent experience).

Tech Stack

• Cloud
• NoSQL
• Python

Benefits

• 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.