Jobs at Accenture

Lead end-to-end technical architecture for complex enterprise programmes across cloud, AI, and enterprise platforms. Define target-state and transition architectures, make build/buy/reuse decisions, govern design standards, and maintain architecture documentation. Engage senior clients, facilitate workshops, guide platform and integration choices, mentor technical teams, oversee delivery alignment, and contribute to architecture practice development. The role requires cloud expertise, distributed systems and security knowledge, AI-enabled development experience, and strong client-facing leadership.

Develop analytical assessments, benchmarking analyses, future-state process designs, and change-impact recommendations for AI-driven business transformation. Design AI integration points, agent behaviors, autonomy levels, and human handoffs within redesigned processes. Support digital and platform solutions, create AI-assisted visualizations and frameworks, improve functional playbooks, and contribute domain expertise in a consulting environment.

Leads the growth and strategy of an enterprise AI practice in Ireland, shaping client transformation agendas, driving strategic pursuits, and building a high-performing AI engineering team. Oversees architecture and delivery of generative AI, agentic AI, and machine learning solutions, while establishing engineering standards, governance, security, responsible AI, and operational best practices. Represents the practice through executive engagement, thought leadership, and industry events.

Designs and delivers scalable batch and streaming data solutions on Azure and Microsoft Fabric. Builds lakehouse, warehouse, and semantic layers for analytics and AI; implements data quality, metadata, lineage, monitoring, security, and CI/CD. Owns technical workstreams from design through production, optimizes performance and cost, manages stakeholders, reviews designs, establishes engineering standards, and mentors data engineers.

Lead the design and development of Power Platform applications, Dataverse solutions, cloud flows, integrations, reusable components, and custom controls. Translate business needs into technical designs, oversee architecture and delivery, enforce security, accessibility, governance, and automated deployment standards, and resolve technical issues. The role also includes code reviews, testing, performance optimization, mentoring developers, and collaboration with architects, product owners, and analysts.

Build, integrate, test, govern, and support production-ready AI agents using Microsoft Copilot Studio and Power Platform. Connect agents to Dataverse, Microsoft 365, APIs, and Azure services while implementing prompts, retrieval, human oversight, authentication, security, responsible AI controls, documentation, ALM, CI/CD, releases, and support processes.

Leads the architecture, design, implementation, and delivery of enterprise-scale full-stack applications. Provides hands-on technical direction, establishes engineering standards, develops .NET and Azure solutions, supports APIs and databases, implements CI/CD and observability, manages technical risks, resolves complex issues, and mentors engineers. Collaborates with architects, product owners, UX teams, and client stakeholders while incorporating AI-assisted development practices.

Leads the design, implementation, security, automation, and operation of Azure cloud platforms supporting analytics and AI workloads. Builds infrastructure-as-code environments, data platform foundations, private connectivity, identity, disaster recovery, monitoring, and governance controls. Oversees technical delivery, troubleshooting, cost optimization, operational readiness, and transition to operations while coaching engineers and collaborating with architects, security teams, application teams, and stakeholders.

Leads enterprise Dynamics 365 and Power Platform architecture across complex client engagements. Shapes solution strategies, supports proposals, defines architecture standards and governance, designs applications, data models, integrations, security, environments and ALM, and assures technical quality. Mentors architects and consultants, guides development teams, resolves complex delivery issues, and advises senior client leadership on technology strategy.

Lead the architecture, design, and delivery of scalable .NET applications hosted on Azure. Mentor development teams, oversee coding standards and delivery quality, resolve technical issues, mitigate risks, and collaborate with architects and product owners. The role operates in an agile DevSecOps environment and promotes secure software design, reusable solutions, continuous improvement, technical documentation, CI/CD, Azure deployments, and effective stakeholder coordination.

Conduct risk-based IT audits and assessments, report findings to leadership and the Audit Committee, and advise business partners on technology and emerging risks. The role covers cybersecurity, cloud computing, AI, automation, IoT, infrastructure, applications, ERP controls, operating systems, and vendor management. It also contributes to audit planning, analytics, process improvements, training, and departmental initiatives, with up to 20% travel throughout Ireland and the EU.

Design, build, and deploy production-grade agentic AI systems at enterprise scale. Lead client engineering engagements, define RAG and multi-LLM standards, own LLMOps (eval, prompt governance, observability), implement cloud-native architectures, and publish reusable patterns. Manage and develop engineering teams and measure agentic system quality across accuracy, latency, safety, and cost.

Embed with client teams to deploy, scale, and operationalize enterprise AI platforms end-to-end. Drive production outcomes (time-to-value, reliability, adoption, scalability), design enterprise AI architectures, build reusable patterns, lead workshops and prototypes, and translate technical solutions into quantifiable business impact for senior stakeholders.

The role involves advising clients on payroll transformation using Workday software, configuring payroll systems, conducting testing, and providing training.

Design, build, and deploy production-grade agentic AI systems: multi-agent orchestration, RAG pipelines, provider abstraction, LLMOps (eval harnesses, prompt versioning, observability), cloud-native deployment (Kubernetes/Docker/CI-CD/IaC), and embed with client teams to deliver reusable patterns and measurable metrics for accuracy, latency, safety, and cost.

Embed with client teams to deploy, scale, and operationalize enterprise AI platforms. Own production outcomes from prototype to production, design enterprise AI architectures across identity, data, security, governance, and build reusable playbooks and accelerators to ensure adoption, reliability, and scalability.