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Mmc

Engineering Manager, GenAI @MarshTech

Cluj-Napoca - Decembrie

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hirly's read of this role

Role family
Engineering management
Seniority
Lead / management
Country
RO
Work mode
On-site / unstated
First seen by hirly
2 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Company:

Oliver Wyman

Description:

We are seeking an experienced Engineering Manager to lead multiple AI delivery pods focused on designing and delivering enterprise-grade, AI-enabled solutions for business stakeholders. This role is accountable for people leadership, delivery outcomes, solution quality, and architectural alignment, while maintaining the technical awareness and judgment needed to guide teams effectively.

You will manage several cross-functional AI pods, each composed of senior, mid-level, and junior engineers. You will work closely with Senior Engineers acting as Tech Leads within pods, as well as shared functions such as QA/Test Engineering, Solution Architecture, and UI/UX, to ensure solutions are delivered quickly, consistently, and in line with enterprise standards.

In parallel, you will contribute to enterprise AI engineering practices and collaborate closely with peers and leaders in the AI CoE, helping translate broader AI strategy into practical, scalable solution delivery.

What you can expect

The Engineering Manager is part of a strategic group of engineering leaders within the organisation, responsible for embodying best practices, quality, and the overall engineering strategic vision.

You are an engineering manager with direct line management responsibility for engineers across multiple AI delivery pods. You are accountable for delivery performance, team health, and the professional development of engineers, while remaining technically credible and engaged at the level required to support sound decision-making.

You help teams translate enterprise AI strategy into practical, scalable solutions and provide solution-level architectural input, ensuring designs align with enterprise standards and support long-term scalability, reuse, and maintainability.

You will enable the delivery of solutions founded on strong engineering principles, including:

  • Security
  • Scalability
  • Reliability
  • Maintainability
  • Testability

What we will count on you to:

Lead and manage AI delivery pods

  • Line-manage engineers across multiple AI delivery pods, providing coaching, feedback, and career development support.
  • Partner with Senior Engineers acting as Tech Leads to ensure strong technical direction and coherent delivery within each pod.
  • Build, support, and retain high-performing, inclusive engineering teams.
  • Ensure pods consistently deliver production-ready enterprise solutions, not just proofs of concept.

Own delivery outcomes, quality, and architectural alignment

  • Own delivery outcomes across pods, balancing speed, quality, and sustainability.
  • Champion strong engineering practices including code quality, testing, CI/CD, observability, and documentation.
  • Ensure solution architectures support security, scalability, reliability, maintainability, and testability, and align with enterprise reference architectures and platform standards.
  • Work closely with shared QA/Test Engineering, Solution Architecture, and UI/UX teams to ensure consistency, reuse, and adherence to standards.
  • Promote reuse of patterns, components, and approaches across pods and the wider organisation.

Provide architectural input and technical oversight

  • Provide solution-level architectural input and technical oversight through design reviews and architectural discussions.
  • Guide Tech Leads and teams in making sound, enterprise-aligned design decisions and trade-offs.
  • Act as an escalation point for complex technical, architectural, or delivery challenges.
  • Help teams apply AI and LLM-based capabilities responsibly within enterprise constraints.

Contribute to enterprise AI engineering leadership

  • Participate in enterprise AI engineering discussions, communities of practice, and standards definition.
  • Share learnings from AI solution delivery to inform broader tooling, patterns, and delivery models.
  • Collaborate with senior engineering leaders, architects, and stakeholders to align AI solutions with organisational goals.
  • Contribute to thought leadership around modern software engineering and applied AI.

Foster a strong engineering culture

  • Champion effective Agile practices that support predictable, high-quality delivery.
  • Create a collaborative, inclusive environment where engineers can do their best work.
  • Support engineers at different career stages, helping them grow and progress along clear career paths.

What you need to have

  • Proven experience as an Engineering Manager or similar role with people-management responsibility.
  • Experience delivering AI-enabled solutions in enterprise environments, including working with production systems that must meet security, scalability, reliability, and governance requirements.
  • Demonstrated success leading and developing engineering teams delivering enterprise-scale software solutions.
  • Strong background in modern software engineering and cloud-based architectures.
  • Experience overseeing multiple initiatives or teams in parallel.
  • Experience working in Agile, cross-functional environments at enterprise scale.
  • Ability to communicate effectively with both technical and non-technical stakeholders.
  • Strong problem-solving skills and a pragmatic, outcome-focused mindset.
  • Familiarity with modern full-stack and cloud-based technology stacks commonly used to deliver AI-enabled solutions (e.g., frontend frameworks, backend services, cloud platforms, data stores, and LLM-based integrations).

What makes you stand out

  • Experience delivering AI-enabled or data-driven solutions, including applied use of LLMs in production environments.
  • Experience with solution architecture and design governance, working in partnership with architects and platform teams.
  • Experience with Agile at scale, Continuous Integration, Continuous Delivery, and Infrastructure as Code.
  • Strong understanding of security-driven design and modern application security practices.
  • Experience with cloud platforms and DevOps practices that support reliability and scalability.
  • Active contribution to engineering communities, shared standards, or cross-team initiatives.

Why join our team

  • The opportunity to lead and scale enterprise AI solution delivery
  • Meaningful influence over how AI solutions are designed, architected, and delivered
  • A leadership role that balances people leadership, delivery ownership, and architectural input
  • A collaborative, inclusive engineering culture with strong peer leadership
  • Ongoing professional development and growth opportunities
  • Competitive compensation and benefits aligned with local market practices

Marsh (NYSE: MRSH) is 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, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to creating 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, or any other characteristic protected by applicable law.

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.

Original posting on Mmc's site ↗

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