4 days ago
Helsinki, FinlandStaff+
Responsibilities
- Lead the architecture and technical design of enterprise AI, generative AI, and agentic AI solutions on Google Cloud.
- Design end-to-end architectures spanning AI models, data, applications, APIs, integration, cloud infrastructure, identity, and security.
- Architect solutions using Vertex AI, Gemini, BigQuery, and other relevant Google Cloud services.
- Define production architectures covering scalability, availability, performance, observability, cost management, security, and regulatory requirements.
- Design MLOps and LLMOps approaches for deploying, evaluating, monitoring, and governing AI models and applications.
- Integrate AI solutions with enterprise applications, data platforms, security architectures, and existing technology landscapes.
- Provide technical leadership across opportunity shaping, architecture, implementation, and production deployment.
- Evaluate managed AI services, foundation models, open-source technologies, and architectural trade-offs.
- Advise clients on responsible and secure AI adoption, including identity and access management, data protection, governance, model risk, and secure AI architecture.
- Contribute to proposals, solution shaping, estimation, reusable architecture patterns, and the AI architecture community.
- Coach architects and engineers and lead architecture discussions across multiple disciplines.
Requirements
- Several years of experience designing and delivering enterprise cloud, data, machine learning, or AI solutions, including leadership of complex technical engagements.
- Strong hands-on architecture experience with Google Cloud Platform, especially Vertex AI and the broader Google Cloud AI ecosystem.
- Experience designing solutions using generative AI and foundation models; Gemini experience is advantageous.
- Strong understanding of data architecture and data engineering, including BigQuery and integration between enterprise data platforms and AI workloads.
- Understanding of production MLOps and/or LLMOps, including deployment pipelines, model and prompt lifecycle management, evaluation, monitoring, and observability.
- Understanding of Google Cloud infrastructure, networking, IAM, and security architecture for enterprise AI workloads.
- Experience integrating AI capabilities with enterprise applications, APIs, data platforms, and existing technology landscapes.
- Experience leading technical teams and architecture discussions across multiple disciplines.
- Ability to translate business objectives into technical architecture and explain trade-offs to senior stakeholders.
- Strong analytical, problem-solving, verbal, and written communication skills in English.
- Master’s or bachelor’s degree in computer science, engineering, information technology, or another relevant field, or equivalent professional experience.
- Residence in Finland is required.
- Finnish language skills are considered an advantage.
- Relevant Google Cloud certifications, such as Professional Cloud Architect, Professional Machine Learning Engineer, or Professional Data Engineer, are considered an advantage.
Tech Stack
Google BigQueryGoogle Cloud Platform
Categories
Solutions Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.