Engineering Associate Manager

The Dock is Accenture's flagship R&D and Global Innovation Centre, based in Dublin's Grand Canal Dock. As an incubation hub for next-generation AI and agentic solutions, we bring together a global community of engineers, data scientists, designers, strategists, and entrepreneurs to solve complex challenges and develop products and services that help organisations adapt to rapid change.

Our teams operate across the full innovation lifecycle, from early exploration and concept validation through to deployment and scale, working in multidisciplinary teams to transform ideas into practical, real-world solutions.

As an Engineering Associate Manager, you will be responsible for leading engineering teams delivering innovative AI-enabled products and solutions. You will provide technical and people leadership, helping teams navigate ambiguity, establish priorities, and deliver high-quality outcomes in a fast-paced innovation environment.

You will work closely with engineering, product, design, data science, and business stakeholders to translate evolving requirements into scalable solutions. While remaining technically informed, your primary focus will be enabling teams to succeed through effective leadership, coaching, decision-making, and delivery management.

This role requires strong technical judgement, the ability to balance short-term delivery goals with long-term sustainability, and a commitment to developing engineering capability across both project teams and the wider organisation.

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• Proven accountability for the delivery and technical outcomes of an engineering team or significant workstream, including taking solutions from early design through deployment and ongoing operation.

• A track record of coaching and developing engineers, delegating meaningful ownership while maintaining appropriate oversight of quality, risk, and delivery outcomes.

• Strong technical judgement across software engineering fundamentals, including system design, APIs, data, testing, cloud-native technologies, and modern delivery practices.

• Experience delivering AI-enabled capabilities in production environments and operating effectively in ambiguous settings, turning evolving requirements into clear priorities and technical direction.

• Ability to evaluate, make, and communicate engineering trade-offs across speed, quality, scalability, security, maintainability, and cost with both technical and non-technical stakeholders.

• Experience leading engineering teams in innovation-led, consulting, research, or product incubation environments where experimentation and delivery need to coexist.

• Strong solution design and architectural experience, with the ability to challenge approaches from early concept through to production-ready implementation.

• Hands-on exposure to real-world deployments of LLM-based solutions, machine learning platforms, or AI orchestration patterns, from experimentation through operational ownership.

• A history of building more than just products by contributing reusable assets, standards, frameworks, accelerators, hiring initiatives, or engineering capability programmes.

• Comfort working within large, matrixed organisations and a genuine curiosity for emerging AI technologies, coupled with the judgement to distinguish practical value from hype.

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