Moody's Corporation
Software Engineer - AI Platform & Agents

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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. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
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.
Skills And Competencies
- 3+ years of experience in backend software development, building scalable, resilient, and production-grade systems
- Hands-on experience developing AI-powered applications, including large language models (LLMs), AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniques
- Proven ability to take AI solutions from concept and experimentation through to production deployment, optimizing for performance, reliability, scalability, and cost
- Strong knowledge of cloud platforms such as AWS, GCP, or Azure, along with containerization and orchestration technologies including Docker, ECS, and Kubernetes
- Proficiency with databases such as PostgreSQL and MongoDB and caching technologies such as Redis for high-performance data storage and retrieval
- Experience designing and building APIs, distributed systems, and event-driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar
- Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred
- Strong problem-solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful solutions that create measurable business value
- Excellent communication and collaboration skills with demonstrated success working across multidisciplinary teams of engineers, data scientists, and product stakeholders
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Education
- Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field
Responsibilities
As a Software Engineer specializing in AI systems, you will help shape the next generation of intelligent applications by building scalable platforms that bring cutting-edge AI capabilities into real-world production environments. Working at the intersection of software engineering and machine learning, you will design and develop systems that power AI agents, large language model applications, and advanced automation solutions used by teams across the business. You will collaborate closely with engineers, data scientists, and product partners to transform innovative ideas into reliable, secure, and impactful products.
- Design and build scalable backend platforms, APIs, and services that power AI applications, intelligent automation solutions, and AI agents
- Develop and deploy advanced LLM-powered applications using techniques such as retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization
- Create robust data and inference pipelines that support both real-time and batch AI workloads at enterprise scale
- Partner with data scientists and machine learning engineers to integrate emerging AI capabilities into production products and services
- Build systems that enable AI agents to reason, automate tasks, interact with tools, and solve complex business challenges autonomously
- Optimize applications for performance, scalability, reliability, and cost efficiency while supporting increasing AI adoption and usage
- Implement engineering best practices around observability, monitoring, testing, security, and operational excellence
- Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement
- Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across multiple teams
- Participate in architecture discussions, technical design reviews, and engineering initiatives that influence the future direction of AI products
- Mentor engineers, share technical expertise, and contribute to a culture of innovation, experimentation, and continuous learning


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About The Team
Our Innovation 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 is made up of a diverse set of engineers, data scientists, and AI specialists who are passionate about solving complex challenges and turning breakthrough ideas into real-world solutions. We operate in agile, highly collaborative squads focused on delivering innovative products that enhance productivity, unlock insights, and create measurable business impact.
Collaboration is at the heart of everything we do. Engineers have the opportunity to work across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment. Joining our team means working on some of the most exciting challenges in applied AI, contributing to products used across the organisation, and being part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
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