Principal Software Engineer-AI

Overview

As Principal Engineer, you will lead the strategy and delivery of mission-critical AI platforms within Moody’s Digital Content and Innovation team. You will shepherd multi-team efforts from prototype to production, shaping scalable, responsible AI solutions built on large language models. You’ll partner with product, risk, andCompliance stakeholders to maximize value while upholding governance and ethics. This is a hands-on leadership role with a strong impact on platform adoption and operational excellence.

Responsibilities

• Lead strategy, delivery, and evolution of AI platforms and intelligent applications across the portfolio
• Define long-term technical strategy and multi-year architecture roadmap for AI platforms
• Grow and organize multiple engineering teams, including managers, leads, and engineers, with delivery accountability
• Drive architectural decisions and integration of AI solutions using LLMs, retrieval augmented generation, and orchestration frameworks
• Establish engineering excellence through architecture reviews, testing standards, observability, security, and MLOps practices
• Own budgeting and cost management including cloud infrastructure, model usage, and tooling investments
• Collaborate with product, risk, legal, compliance, and audit to implement responsible AI governance
• Mentor and develop engineering talent, including succession planning and leadership cultivation
• Define and report on metrics for platform adoption, reliability, and business impact
• Help translate applied AI into scalable, production-ready capabilities across Moody’s products

Key requirements

• 12+ years of software engineering experience with 5+ years leading engineering teams
• Experience leading multiple teams and managing managers, tech leads, and staff engineers
• Deep technical depth in TypeScript, Python, or C#, with ability to engage in architecture and code reviews
• Expertise in enterprise AI applications built on large language models, including agents and retrieval augmented generation
• Hands-on experience building AI/ML applications and taking them to production or platforming
• Production AI systems experience at scale with observability, cost and capacity planning, and incident response
• Production distributed systems on AWS/Azure with reliability and observability focus
• Cloud-native, serverless, event-driven architectures, data/inference pipelines, relational/NoSQL/vector databases
• Track record of owning multi-year technical strategy and architectural roadmaps
• Strong leadership in AI governance, responsible AI adoption, and risk management

• Leadership and people management
• Strategic thinking and cross-functional collaboration
• Effective communication with technical and non-technical stakeholders
• TypeScript
• Python
• C#

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