Assistant Director - Applied AI Engineer

Assistant Director - Applied AI Engineer

Full-Time 80000 - 100000 € / year (est.) No home office possible
Moody's Investors Service

At a Glance

  • Tasks: Design and deliver innovative AI solutions that tackle real-world business challenges.
  • Company: Join Moody's, a leader in risk assessment and AI innovation.
  • Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative team environment with a focus on continuous learning and development.
  • Why this job: Be at the forefront of AI technology and make a meaningful impact.
  • Qualifications: Experience in applied AI, strong problem-solving skills, and effective communication.

The predicted salary is between 80000 - 100000 € per year.

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

  • Strong problem-solving capability, with the ability to break down ambiguous business problems, form and test hypotheses, reason from first principles, and determine when AI is the right solution versus simpler alternatives.
  • Confident stakeholder communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences, present trade-offs to senior leaders, and translate effectively between engineering, product, and business teams.
  • Proven ability in requirements gathering and user experience design, including eliciting and documenting business needs, designing intuitive AI-powered experiences, and incorporating iterative user feedback.
  • Adaptability and comfort working through ambiguity, adjusting technical and delivery approaches as new evidence, feedback, or business priorities emerge.
  • Hands-on applied AI engineering experience, including proficiency in Python, JavaScript, or similar languages, and practical use of modern GenAI and agent frameworks such as LangChain, LlamaIndex, or SmolAgents.
  • Experience building, deploying, and maintaining production-grade AI systems that deliver measurable business value.
  • Working knowledge of data management, including data architecture, governance, and privacy considerations, with experience using tools such as Pandas, NumPy, SQL, and a major cloud platform (AWS, Azure, or GCP).
  • Practical experience with production reliability, including monitoring, release gates, rollback strategies, incident response, and managing trade-offs between quality, latency, and cost.
  • Experience evaluating emerging AI technologies and frameworks, designing structured bake-offs, and making evidence-based recommendations.
  • Demonstrates deep expertise in applying AI responsibly, including consideration of ethical use, risk management, and governance in production environments.

Education

  • Bachelor’s degree required in Computer Science, Data Science, Statistics, Mathematics, Business, Information Systems, or a related field.
  • Master’s degree or PhD welcomed, or equivalent demonstrable experience in applied AI.
  • Demonstrated commitment to continuous professional development in AI or machine learning through certifications, publications, conference participation, or similar evidence of staying current in the field.

Responsibilities

  • Operate as a senior individual contributor who partners closely with the business to design, deliver, and embed applied AI solutions from initial concept through to reliable production use.
  • Partner with business stakeholders and workstream leads to understand operational challenges and translate them into AI solutions aligned with business priorities.
  • Present progress, options, risks, and trade-offs clearly and confidently to senior leaders, keeping stakeholders and delivery teams aligned.
  • Own the end-to-end user journey for solutions, including requirements gathering, experience design, rollout planning, user training, and feedback capture.
  • Frame and structure problems rigorously before designing solutions, ensuring clarity of scope, assumptions, and success criteria.
  • Design, build, and deploy AI-powered solutions such as automation, intelligent data pipelines, predictive analytics, and custom internal tools, holding work to a quality standard appropriate for the financial services industry.
  • Own the reliability of AI services in production, including defining release gates, monitoring, rollback strategies, and incident response processes.
  • Profile system performance, manage token and compute usage, and balance solution quality, latency, and cost.
  • Apply responsible AI practices, including privacy, security, and bias-mitigation controls, and participate in required reviews, sign-offs, and documentation.
  • Run structured evaluations and bake-offs of models, tools, and frameworks, and provide evidence-based recommendations.
  • Contribute to the Applied AI team’s shared practice through documentation, demos, reference patterns, walkthroughs, and mentoring of more junior engineers.
  • Plan and execute work with strong delivery discipline, surfacing risks and dependencies early and landing deliverables on time and within scope.

About the Team

The Applied AI team harnesses the latest advances in generative AI to amplify Moody’s Analytics’ capabilities across the enterprise. By combining strong AI product and engineering expertise with deep business understanding, the team focuses on high-impact internal workflows, beginning with sales and extending across customer service, marketing, product strategy, operations, legal, and finance. The team’s mission is to create shared institutional intelligence about customers—their needs, behaviors, and feedback—enabling sharper decisions, faster actions, and long-term success for the business.

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.

Assistant Director - Applied AI Engineer employer: Moody's Investors Service

At Moody's, we pride ourselves on fostering an inclusive and innovative work culture that empowers our employees to thrive. As a leader in the financial services industry, we offer exceptional growth opportunities in applied AI engineering, alongside competitive benefits and a commitment to professional development. Our collaborative environment encourages diverse perspectives and creative problem-solving, making Moody's an ideal place for those looking to make a meaningful impact in their careers.

Moody's Investors Service

Contact Detail:

Moody's Investors Service Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Assistant Director - Applied AI Engineer

Tip Number 1

Network like a pro! Reach out to current or former employees at Moody's on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.

Tip Number 2

Prepare for the interview by practising your storytelling skills. We want to hear how you've tackled complex problems in the past, especially those involving AI. Make it relatable and show how your experience aligns with Moody's mission.

Tip Number 3

Show off your adaptability! Be ready to discuss how you've navigated ambiguity in previous roles. Moody's values flexibility, so share examples of how you've adjusted your approach based on new evidence or feedback.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Moody's team and contributing to their innovative work.

We think you need these skills to ace Assistant Director - Applied AI Engineer

Problem-Solving Skills
Stakeholder Communication
Presentation Skills
Requirements Gathering
User Experience Design
Adaptability
Applied AI Engineering

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight how your skills align with the role. We want to see how you can turn those risks into opportunities, so don’t hold back on showcasing your problem-solving capabilities!

Showcase Your Technical Skills:Since this role is all about applied AI engineering, be sure to mention your hands-on experience with languages like Python or JavaScript. We love seeing practical examples of how you've built and deployed AI systems that deliver real business value.

Communicate Clearly:Remember, you’ll need to explain complex concepts to non-technical folks. Use clear language in your application to demonstrate your ability to bridge the gap between technical and business teams. We’re looking for candidates who can present ideas confidently!

Emphasise Continuous Learning:We value candidates who are committed to staying current in the field of AI. Mention any certifications, publications, or conferences you’ve attended. Show us that you’re not just resting on your laurels but actively investing in your professional development!

How to prepare for a job interview at Moody's Investors Service

Know Your AI Stuff

Make sure you brush up on your applied AI knowledge, especially around the tools and frameworks mentioned in the job description. Be ready to discuss your hands-on experience with Python, JavaScript, and any GenAI frameworks you've used. This will show that you can hit the ground running!

Communicate Like a Pro

Since you'll need to explain complex concepts to non-technical folks, practice simplifying your explanations. Think about how you would present your past projects to someone without a tech background. Clear communication can set you apart from other candidates.

Showcase Problem-Solving Skills

Prepare to discuss specific examples where you've tackled ambiguous problems. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your strong problem-solving capability and how you approach challenges.

Emphasise Adaptability

Be ready to talk about times when you've had to adjust your approach based on new evidence or feedback. Moody's values adaptability, so sharing experiences where you've thrived in uncertain situations will resonate well with the interviewers.