AI Operations Specialist

AI in this role

prompt-engineeringragml-opsai-safety

Company:

Guy Carpenter

Description:

We are seeking a talented individual to join our Guy Carpenter Operations / Operational Change team at Guy Carpenter. This role will be based in New York or Chicago. This is a hybrid role that has a requirement of working at least three days a week in the office.

This strategic, execution-focused colleague will drive AI solutions across Guy Carpenter’s reinsurance operations. You will be at the forefront of AI-driven process reengineering, helping shape and execute AI strategy and process redesign across the organization. The successful candidate will identify opportunities, design solutions, and deliver production-grade AI capabilities that create measurable business value.

We will count on you to:

Identify, prioritize, and champion high-impact AI use cases across the reinsurance value chain, translating operational pain points into scalable AI opportunities
Execute AI strategy for reinsurance broking operations, partnering across Broking, Distribution, Analytics, CSS/Operations, and IT to deliver outcomes
Coordinate cross-functional teams to deliver generative AI solutions from ideation through production, ensuring strong execution discipline and adoption
Translate complex technical concepts (e.g., LLMs, prompt engineering, RAG, MLOps) into clear business value propositions and compelling narratives for stakeholders and leaders
Establish and promote best practices across the AI lifecycle, including responsible AI principles, governance, and model risk considerations
Drive change management and capability-building initiatives, including training materials, knowledge resources, and communities of practice to accelerate adoption and impact

What you need to have:

8–10 years of experience in process re-engineering, data science, AI/ML, product management, strategy, operations consulting, or related experience
Deep technical expertise in machine learning and generative AI (LLMs, prompt engineering, RAG) with hands-on implementation experience, plus familiarity with MLOps practices and tools
Proven track record translating business problems into AI use cases and delivering measurable value in financial services, insurance, or reinsurance
Exceptional stakeholder management, influencing, and communication skills, including ability to build consensus and drive change with senior leaders

What makes you stand out:

Product management experience defining product vision, managing roadmaps, prioritizing features, and launching successful solutions with strong execution delivery
Experience implementing AI solutions for (re)insurance workflows, including familiarity with reinsurance analytics tools and/or catastrophe modeling platforms (RMS, AIR, CoreLogic)
Advanced degree (Master’s/PhD) and/or relevant professional certifications in AI/ML, product management, or insurance qualifications (e.g., ACAS, FCAS, CII)

Why join our team:

We help you be your best through professional development opportunities, interesting work and supportive leaders.
We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

At Guy Carpenter, a Marsh business, you can be your best. We work on challenges that matter with colleagues who help bring out our best. Our uniquely collaborative environment will empower you to focus on your personal and professional success, learning from top specialists in the (re)insurance industry and leading you towards a rewarding and impactful career.

Guy Carpenter is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information about Guy Carpenter, visit guycarp.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting reasonableaccommodations@marsh.com.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

How we rate this

AI Operations Specialist at Marsh McLennan rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGML OpsAI Safety

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, RAG, ML Ops, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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