Find Ai/ml engineer Jobs in Sandyford County Dublin

Engineering Lead
Accenture —Dublin, County Dublin
- Full-time
- System design
- Master's degree
- AI
Lead Program Security Engineer
Mastercard —Dublin, County Dublin
- Full-time
- DevOps
- AI
- Leadership
Sr Engineering Manager, Info Sec
eBay Inc. —Dublin, County Dublin
- Full-time
- Azure
- AWS
- Product management
Senior Sales Operations Analyst
MongoDB —Dublin, County Dublin
- Hybrid work
- Azure
- Sales
- SQL

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Engineering Lead

Accenture -
Dublin, County Dublin

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Job details

Full-time

Qualifications

CI/CD
Law
System design
Master's degree
AI
SDLC

Full job description

Engineering Lead

level

Experienced

Engineering Lead @The Dock

About The Dock

The Dock is Accenture's flagship R&D and Global Innovation Center, based in Dublin's Grand Canal Dock. As an incubation hub for the next generation of AI and GenAI agentic solutions, we bring together a global community of business strategists, designers, engineers, data scientists, and entrepreneurs to solve some of the world's hardest problems and build products and services that help industries adapt to rapid change.

Our teams operate across the full innovation spectrum — from early exploration through to real-world deployment — working in tight, multidisciplinary pods that turn ideas into things clients can actually use.

About the

As an Engineering Lead, you will own and deliver engineering workstreams end‑to‑end, from early technical discovery through to implementation and handover. You will operate in an innovation‑driven environment where requirements may be incomplete and timelines constrained; the expectation is that you bring structure, make trade‑offs, and deliver working software with a clear path to deployment and ongoing support.

This is a hands‑on engineering . Success is not just writing code, but delivering working solutions end‑to‑end. You will drive delivery by personally owning significant parts of the implementation, shaping scope and approach in collaboration with peers, and ensuring solutions can be deployed, operated, and evolved.

You will work closely with data scientists, engineers, and product partners to turn requirements into AI-enabled capabilities embedded in real products. You will stay current on AI tooling, but apply it with the judgement of an engineer, not the enthusiasm of an early adopter. That means balancing what's fast to build against what the team (or client) will have to maintain six months later.

You will also contribute to team capability through code reviews, pairing, shared patterns and standards, and practical improvements to how the team builds and ships software.

Desired Skills & Experience

5–8 years’ experience as a software engineer delivering production‑grade systems.

Proven experience owning and delivering technical workstreams end‑to‑end, from early solution design through implementation and handover.

Strong software engineering fundamentals, including system design, APIs, data management, testing, and code quality.

Hands‑on experience building and integrating AI‑enabled capabilities into products or platforms (application and integration focused, not research).

Demonstrated ability to operate effectively in ambiguous problem spaces, translating evolving requirements into clear technical approaches.

Experience across the full software development lifecycle, including operational and support considerations.

Familiarity with cloud‑native environments and modern delivery tooling (CI/CD pipelines, containers, managed services).

Proven ability to make and clearly explain engineering trade‑offs across speed, quality, scalability, security, and cost.

Experience shaping technical approaches with awareness of delivery cost, sustainability, and downstream effort.

Strong experience working in cross‑functional teams, partnering with product, design, data science, and commercial colleagues.

Ability to communicate technical concepts clearly to non‑technical stakeholders.

Takes on technical ownership and decision‑making while remaining a hands‑on technology contributor.

Extras We’d Love to See

Experience delivering work in an innovation‑led, consulting, or product incubation environment.

Strong solution design skills — able to take a problem from concept through to a technical architecture that holds up under review.

Exposure to LLM‑based systems, ML platforms, or AI orchestration patterns used in real deployments.

Demonstrated contribution to reusable assets, accelerators, or shared engineering standards.

Experience operating within a large, matrixed organisation with shared ownership and dependencies.

Naturally curious about the wider AI landscape, and tests assumptions in code. Enjoys the loop between "what's out there" and "does it actually solve our problem" — and flags the gaps along the way.

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