Moody's Corporation
Senior Software Engineer-AI
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Skills And Competencies
- 5+ years of software engineering experience designing, coding, testing, and operating production-grade backend services and cloud-native applications
- Strong coding proficiency in TypeScript, Python, C#, or similar technologies, with experience building scalable application programming interfaces, microservices, and distributed systems
- Practical experience building enterprise AI applications using large language models, including agents, retrieval augmented generation, orchestration frameworks, and model optimization
- Demonstrated ability to own services, components, or features end to end, from technical design through production deployment and ongoing operation with limited supervision
- Hands-on experience with cloud-native technologies, serverless applications, event-driven architectures, data pipelines, relational and NoSQL databases, vector databases, observability tooling, and automated deployment pipelines
- Solid understanding of algorithms, data structures, scalability, reliability, performance optimization, security best practices, and engineering trade-offs
- Experience mentoring engineers through code review, pairing, debugging, documentation, and the promotion of engineering excellence through testing and continuous improvement practices
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
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Education
- Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience
Responsibilities
- Designs, builds, and operates the services and AI-powered features behind Moody's intelligent data products as a senior contributor within the Digital Content and Innovation organization.
- Design, code, test, and operate backend services, application programming interfaces, data pipelines, and inference pipelines that support real-time and batch AI workloads
- Own the delivery of assigned features and components end to end, from technical design through deployment, monitoring, production support, and continuous improvement
- Build and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integration
- Contribute to technical designs, participate in design reviews, and identify risks, constraints, trade-offs, and alternative approaches
- Maintain engineering excellence through automated testing, code reviews, observability, monitoring, alerting, operational readiness, and participation in on-call support
- Apply machine learning operations practices, including prompt versioning, automated evaluation, deployment pipelines, monitoring, and production issue resolution
- Partner closely with product managers, data scientists, machine learning engineers, and fellow engineers to translate requirements into reliable software solutions
- Mentor engineers, contribute to shared frameworks and developer tooling, document system designs and operational runbooks, and promote responsible AI practices across delivered features
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About The Team
Our Digital Content and Innovation (DC&I) team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing. The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact. Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices. By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.
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