Principal AI Architect

DataJobs; Amsterdam; On-site; EUR 170,000 - 230,000; Full time

Job summary

Accenture is seeking a Principal AI Architect to own the end-to-end architecture of advanced AI platforms. You will work with CIOs, CTOs, and senior leaders to shape the enterprise AI strategy, ensuring alignment with business objectives and enterprise-grade standards.

You will lead multiple domain architects, govern architectural patterns, and deliver production-ready AI systems with strong security, observability, and governance across domains.

Qualifications

• Experience designing & deploying enterprise-grade AI solutions (agentic, generative & classical AI/ML).
• Experience with LLM and Generative AI space.
• Architecting and operationalizing LLM-driven architectures and patterns.

Responsibilities

• Shape the enterprise AI strategy with business leaders.
• Lead assessments and craft implementation roadmaps.
• Own end-to-end technical solutions for complex AI platforms.
• Define memory, context, and governance across AI ecosystems.
• Produce architectural artifacts and guidance for delivery at scale.

Skills

Enterprise AI architecture

LLM & Generative AI

Cloud vendor experience

Machine learning & NLP

Architectural governance

Education

Bachelor's Degree or equivalent

Job description

Role

Principal AI Architect

Location: Netherlands

Career Level: Associate Director

#LI-EU

As a Lead or Principal AI Architect, you serve as the definitive technical authority on AI architecture within client engagements and across the practice. You own the complete, end-to-end architecture of advanced AI platforms and solutions. This spans classical machine learning, generative AI, and agentic systems. You ensure every domain of the architecture is cohesively designed, technically sound, and purposefully aligned to client business objectives and enterprise-grade standards. You operate at the executive level, working closely with CIOs, CTOs, and senior business leaders to help shape and articulate the enterprise AI strategy. You connect business goals, priorities, and transformation agendas to a coherent technical vision. You make sure AI investments are purposeful, sequenced, and positioned to deliver lasting competitive advantage. This strategic partnership with client leadership makes you both a trusted advisor and a principal architect.

You lead and integrate the work of multiple domain architects and subject matter specialists. Their areas include agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, and model platforms and inference. You provide the architectural vision, technical governance, and cross-domain coherence that binds their contributions into a unified, enterprise-ready system. You set the architectural direction, resolve cross-domain tensions, and make the critical design decisions that shape the entire AI solution.

Beyond client delivery, you are a thought leader and authority in AI. You stay at the forefront of the latest research, emerging standards, industry innovations, and evolving technology landscapes. You shape the practice's AI architecture point of view and contribute to internal knowledge, frameworks, and reusable assets. You represent the firm externally through publications, conference engagements, and client advisory conversations. Clients, practice leadership, and peers seek your perspective on where AI is heading.

You evaluate and make definitive decisions on design patterns, technical frameworks, reference architectures, and technology selections. You balance innovation with pragmatism to deliver systems that are robust, scalable, and built to last. This includes architectural oversight across AI agent ecosystems, covering multi-agent orchestration, tool use, skills use, and memory systems. It also covers foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You are accountable for the complete architecture meeting the most rigorous non-functional requirements across security, observability, governance, performance, and scalability. You address these concerns holistically and consistently across all domains.

You produce and govern the authoritative architecture artifacts that guide delivery at scale. These include architecture decision records (ADRs), reference architectures, component and data flow diagrams, and integration specifications. You provide executive-level technical leadership. This gives cross-functional engineering teams, domain architects, and client stakeholders the clarity and confidence to execute. You help the most ambitious clients adopt, scale, and lead with AI. You set a standard for what advanced AI architecture can and should look like, and you deliver transformational, lasting business value.

What you do

• Partner with CIOs, CTOs, and business leaders to shape the enterprise AI strategy, connecting business goals to a coherent, sequenced technical vision
• Lead enterprise AI assessments and build enterprise AI implementation roadmaps that sequence investments for lasting competitive advantage
• Own the complete, end-to-end technical solution for complex AI platforms, ensuring every domain is cohesively designed and aligned to business objectives and enterprise standards
• Translate the governing architecture principles into a concrete, defensible technical solution that domain teams build against
• Build innovative prototypes and proofs of concept hands-on, using emerging technologies to de-risk decisions and prove value early
• Perform technology assessments and comparisons, making definitive, evidence-based recommendations on tools, frameworks, and platforms
• Set the architectural direction for model- and tool-agnostic multi-agent ecosystems: orchestration, memory, and tool/skill use, governed through a registry-bound AI Gateway
• Establish the agent registry and certification model that mandates no uncertified agent reaches production
• Define memory as a first-class abstracted platform service, decoupled from any underlying vendor engine
• Define the foundation model and inference strategy: adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing
• Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms
• Own the architecture of the enterprise context layer: knowledge graphs, ontologies, vector search, and semantic retrieval, grounding the solution in client knowledge
• Set the design direction for context assembly and memory that manages prompts, context windows, and conversational state across the platform
• Be accountable for security, governance, observability, performance, and scalability, addressed holistically and consistently across every domain
• Establish the identity and authorization model: per-agent identity, IAM/IAP binding, and defense-in-depth enforcement
• Define the layered guardrail framework applied at every boundary, balancing protection with performance
• Govern the MCP control plane (registry, gateway, and risk scoring) across all internal and third-party servers
• Mandate adopt-over-build for productized evaluation and observability stacks
• Establish FinOps as a first-class concern: usage labelling, gateway-enforced budgets, and cost-per-archetype as a planning input
• Make the definitive decisions on design patterns, reference architectures, frameworks, and technology selections, balancing innovation with pragmatism
• Lead and integrate the work of domain architects and specialists, resolving cross-domain tensions into a unified, enterprise-ready system
• Build the practice's reusable reference architectures, frameworks, and assets, with a deliberate adopt-over-build stance
• Conduct deep-dive architecture workshops and working sessions with client executives and engineering teams
• Produce and govern the authoritative architecture artifacts (blueprints, reference architectures, ADRs, and integration specifications) that guide delivery at scale
• Serve as a recognized thought leader in AI, shaping the practice's point of view and representing the firm externally through publications and conference engagements

What you bring

Education

• Bachelor's Degree or equivalent

Basic (required) qualification

• Significant experience in designing & deploying enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor.
• Experience in the LLM and Generative AI space.
• Professional experience architecting and operationalizing LLM driven application architecture patterns.
• Solid experience in engineering, machine learning, deep learning and NLP solutions and applications.
• Demonstratable experience as a machine architect in the industry designing big data, machine learning. large scale analytical engineering solutions

About the employer

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services, creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com

Equal Employment Opportunity Statement

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