Oliver Wyman - Digital - AI Product Owner - Dubai/Abu Dhabi
Marsh McLennan is hiring an Oliver Wyman - Digital - AI Product Owner - Dubai/Abu Dhabi (United Arab Emirates). Level rates it ; you can apply on Marsh McLennan.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Bedrock and AI safety.
- Level lists 615 other open roles at Marsh McLennan.
- The role was posted in the last few days.
AI in this role
Company:
Oliver WymanDescription:
Who We Are
Oliver Wyman Digital is a dedicated practice within Oliver Wyman, we deliver world-class products that give our clients a competitive edge and our mission is to leave a positive impact on the world. We have mixed agency skills with our consulting roots in order that we can best answer some of the largest companies’ toughest questions. Our global dynamic team deliver at the highest levels across many specialist skill sets including Design, Data Science & Analytics, Project Delivery and Engineering. We’re committed to growth that provides our people the most exciting and fulfilling opportunities and we are looking for more people to join us.
The Role And Responsibilities - AI Product Engineer
As an AI Product Engineer, you will build the AI products and agentic solutions behind Oliver Wyman's AI-first transformation work, for our clients and for the firm. You own how an AI product is built, secured, and made reliable: from data and retrieval, through agent orchestration and integration, to user interfaces, deployment, evaluation, and ongoing improvement.
You will work in small, multidisciplinary teams alongside AI Product Owners, consultants, industry experts, and client teams, building on live engagements. The role suits engineers who want to ship production-grade AI, see its business impact first-hand, and develop the breadth to lead complete AI products.
What You Will Do
· Full-stack AI products: Develop and integrate user interfaces, backend services, and APIs into complete AI applications, applying appropriate frontend frameworks and user experience principles.
· Agent development and context engineering: Build single and multi-step agents with tools, state, memory, and human checkpoints. Design, test, and optimize agent instructions, context, memory, and tool specifications to improve task completion, reliability, latency, and cost.
· Reliable agent execution: Design agent workflows with durable state, resumability, failure recovery, safe retries, timeouts, and rollback or compensation for actions that cannot simply be reversed.
· Data and knowledge engineering: Build retrieval and knowledge pipelines, prepare structured and unstructured data, and design knowledge stores with appropriate data quality, lineage, protection, and access controls.
· Architecture and integration: Design, build and deploy AI applications on cloud platforms such as AWS, including compute, storage, databases, networking and containerized services. Integrate with enterprise systems through APIs and standard integration patterns, supporting client cloud and on-premise environments.
· Security and AI safety: Apply secure engineering and least-privilege access, and design permission boundaries, handling of untrusted content, connector security, and isolation between clients or tenants. Support IT, Risk, and Legal approvals.
· Evaluation and operations: Build evaluation and regression-testing practices using representative tasks, execution traces, and production feedback. Monitor quality, latency, and cost; design for maintainable operations and work with client technology or platform teams to support products in production.
· Collaboration and client impact: Translate product objectives into sound technical decisions with AI Product Owners, explain trade-offs and risks to non-technical stakeholders, and prepare client teams to run what we build.
· Continuous improvement: Use AI coding tools productively while owning the quality of everything you ship, contribute reusable components and standards, and, as your experience grows, lead workstreams and mentor others.
Skills And Qualifications
We hire across experience levels and assess what candidates can demonstrate. For early-career hires, the priority is strong coding fundamentals, hands-on AI application experience, and sound technical judgement. Complex architecture, production operations, and team leadership can develop with experience. We look for most of the following:
· A degree in computer science, engineering, or a related field, or equivalent practical experience.
· Demonstrated software engineering experience through employment, independent projects, coursework, or open-source contributions; production delivery experience is valued for more senior candidates.
· Strong coding skills in Python and/or TypeScript, including readable code, debugging, source control, and automated testing; exposure to code review and CI/CD is an advantage.
· Evidence of building working LLM-powered application or agent, using tools or APIs, retrieval, or prompt and context design, and being able to explain what worked and what failed.
· Ability to develop software components and integrate with APIs, with a willingness to grow across user interfaces, backend services, and full-stack delivery.
· Foundational data skills, including SQL and working with structured or unstructured information; deeper pipeline and knowledge engineering can develop in the role.
· Hands-on experience with cloud platforms, preferably AWS, including deploying applications, managing cloud services and working with containers, APIs and cloud infrastructure.
· Understanding of cloud security, identity and access management, networking, monitoring and cost optimization.
· A security-first mindset and awareness of AI-specific risks, such as prompt injection, unsafe tool use, secrets exposure, and data leakage.
· Understanding of software testing and why agent outputs require scenario-based evaluation, including both expected and failed behaviours.
· Product curiosity and the ability to explain technical decisions and trade-offs to technical and non-technical colleagues.
· Excellent written and verbal communication in English.
Nice To Have
· Experience with multi-agent orchestration, complex enterprise integrations, vector or graph databases, or observability tooling.
· Experience with AWS services such as Bedrock, Lambda, ECS/EKS, S3, RDS, IAM and CloudWatch, or equivalent services on Azure or Google Cloud.
· Experience with infrastructure as code (e.g., AWS CDK), automated cloud deployments and enterprise cloud security practices.
· Familiarity with AI security and governance frameworks
· Experience in consulting, client-facing, startup, or regulated and government environments.
· A portfolio of code, working demos, or shipped products that illustrates individual contributions.
Why work at Oliver Wyman?
Working as part of our global, entrepreneurial company, you will do meaningful work from day one. We are looking for individuals who challenge the norm, and constantly strive to build something new for the firm and the world around us.
At Oliver Wyman, there's no "one size fits all" - we hire exceptional people and help them thrive through a built-in support network, flexible career paths, and no artificial barriers to advancement.
We have a collaborative, supportive and impactful team environment - we want you to bring your authentic self and enjoy working alongside diverse and down-to-earth colleagues who do serious work, but don't take themselves too seriously.
Our Oliver Wyman Values
We create breakthroughs to achieve the amazing
Be brave
We stand behind our beliefs while exploring what drives them. We stand up for what is right and persevere through difficulty. We venture into the unknown, staying open to our greatest possibilities.
Lead with heart
We build relationships with clients and colleagues that last, grounded in transparency, authenticity, and trust. We love what we do and have fun while we do it. And we combine this passion with rigor and skill to drive sustainable performance.
Strive for breakthroughs
We bring deep expertise and profound curiosity to the pursuit of ambitious ideas and uncommon insights. We ask bigger questions, seek diverse perspectives, and challenge ourselves to find the most powerful and sustainable solutions.
Work as one
We succeed as a unified team of colleagues and clients, achieving together what separately would be beyond our reach. We care for and develop one another. We learn from differences, overcome divisions, and celebrate our shared achievements.
Own our impact
We act as entrepreneurs and stewards of the firm. We own the journey, acting with integrity at every step. And we own our impact, holding ourselves to the highest standards to deliver stronger results for our clients, better opportunities for each other and lasting change for society.
Oliver Wyman is a global leader in management consulting. With offices in more than 70 cities across 30 countries, Oliver Wyman combines deep industry knowledge with specialized expertise in strategy, operations, risk management, and organization transformation. The firm has more than 7,000 professionals around the world who work with clients to optimize their business, improve their operations and risk profile, and accelerate their organizational performance to seize the most attractive opportunities. Oliver Wyman is a business of Marsh McLennan [NYSE: MMC]. For more information, visit www.oliverwyman.com. Follow Oliver Wyman on X @OliverWyman.
How we rate this
Oliver Wyman - Digital - AI Product Owner - Dubai/Abu Dhabi at Marsh McLennan rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Walk me through how you've used Bedrock in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Safety and Bedrock. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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