At Moody’s, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
An Applied AI Engineer who specializes in designing and implementing comprehensive solutions that leverage cutting-edge AI with a deep understanding of business needs. Acts as a senior technical partner embedded within business units to identify strategic opportunities and build scalable, enterprise-grade AI solutions. Focuses on capturing complex business requirements, advanced application design and development, and robust scalable infrastructure. Builds efficient pipelines and interfaces while ensuring optimal system performance, security, and regulatory compliance. Captures and leverages organizational knowledge to transform raw data into actionable insights, aligning AI platforms with strategic business objectives and driving measurable business impact.

SKILLS AND COMPETENCIES

Advanced Programming Skills: Proficiency in Python/Javascript or similar, with demonstrated leadership in implementing enterprise-scale frameworks like LangChain, SmolAgents, LlamaIndex, or similar. Experience architecting and deploying production AI systems.
Generative AI: Demonstrated experience (2-3) leading generative AI initiatives and strategy development. Proven track record of translating AI research into business value.
Strategic Data Management: Advanced proficiency in enterprise data architecture, including experience with data governance, privacy frameworks, and large-scale data processing using tools like Pandas, NumPy, SQL, and cloud platforms (AWS/Azure/GCP).
Emerging Technology Evaluation: Experience evaluating emerging AI technologies, and establishing best practices from academic and industry sources. Ability to assess technology risks and opportunities.
Business Strategy and Problem-Solving: Proven ability to identify high-impact business problems, design comprehensive AI solutions, and lead cross-functional teams through complex implementation challenges.

EDUCATION

Advanced Degree: MSc/PhD in Computer Science, Statistics, Economics, Data Science, Mathematics, Financial Engineering, or related quantitative field.
Professional Development: Demonstrated commitment to continuous learning in AI/ML through certifications, publications, or conference participation.
Leadership Foundation: Evidence of technical leadership capability, business acumen development, and successful track record of driving organizational change.

Strategic Business Partnership: Embed with senior leadership across business units to understand complex organizational challenges and identify high-impact AI transformation opportunities that align with strategic objectives.
Enterprise Solution Architecture: Design, build, and deploy comprehensive AI-powered solutions including advanced automation frameworks, intelligent data pipelines, predictive analytics platforms, and custom enterprise tools that meet stringent financial industry standards.
Technical Leadership and Governance: Serve as the senior technical authority and AI strategist for assigned business units, establishing AI best practices, security protocols, and compliance frameworks.
Applied AI Team Collaboration: Lead participation in the Applied AI team, driving knowledge sharing initiatives, establishing technical standards, and mentoring junior engineers across multiple business units.
Organizational Change Management: Drive adoption of AI solutions at scale, designing training programs for diverse user groups and managing the organizational change process for AI tool implementation.
Strategic Portfolio Management: Oversee multiple concurrent AI initiatives, managing project timelines, resource allocation, and stakeholder expectations while ensuring alignment with business priorities.