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Senior Infrastructure AI Specialist

Accenture -
Bruxelles

Soumettre votre candidature

Détails de l'emploi

Temps plein

Avantages

Éco-chèques
Assurance hospitalisation
GSM de fonction

Qualifications

Français
TensorFlow
Certification ITIL
Infrastructure cloud
Microsoft Excel
Azure
Gestion des incidents
Internet des objets
Kubernetes
Ansible
PyTorch
Vision par ordinateur
Google Cloud Platform
Master
Bases de données
AWS
Machine learning
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Deep learning
ServiceNow
Intelligence artificielle
Python

Description complète du poste

The role

As a Senior Infrastructure AI Specialist, you will define the strategy and lead the design and delivery of AI and generative AI capabilities embedded within infrastructure platforms. You will architect scalable MLOps and GenAIOps frameworks, drive AI-powered observability and automation programmes, and act as the technical authority for AI integration across cloud infrastructure. You will advise clients on their AI-driven infrastructure transformation roadmaps, contribute to business development, and mentor junior specialists within the practice.

Key Responsibilities

Define and drive the AI/GenAI strategy for infrastructure services: AIOps, predictive operations, and intelligent automation.
Architect and deliver production-grade MLOps and GenAIOps platforms on cloud (AWS, Azure, GCP).
Design scalable AI pipelines for model training, evaluation, deployment, and lifecycle governance.
Lead the implementation of GenAI-powered infrastructure use cases: incident prediction, capacity planning, anomaly detection, and self-healing automation.
Architect RAG systems, LLM fine-tuning pipelines, and agentic AI workflows for infrastructure automation.
Oversee GPU/TPU compute infrastructure provisioning and optimisation for AI/ML workloads.
Implement AI governance frameworks: model explainability, bias auditing, and regulatory compliance (EU AI Act).
Define the MLOps tooling strategy: feature stores, experiment tracking, model registries, and inference serving platforms.
Define and optimize AI FinOps and TokenOps practices, including model cost control, token consumption management, GPU utilisation, and chargeback/showback mechanisms.
Ensure AI security, data protection, model security, and secure integration with enterprise infrastructure platforms.
Collaborate with infrastructure, cloud, network, security, and operations teams to industrialize AI solutions within production environments.
Act as a technical advisor to client leadership on AI infrastructure integration and emerging AI trends.
Mentor junior AI specialists and build internal AI capabilities across the infrastructure practice.
Contribute to business development by shaping AI-enabled infrastructure propositions and use cases.

Who We Are

Accenture is a leading global professional services company that helps organizations build their digital core, optimize operations, accelerate growth and enhance services. We combine deep industry expertise with advanced technology capabilities in cloud, data & AI, security and intelligent platforms.

In Belgium and Luxembourg, our teams work with leading organizations across the public and private sectors to drive innovation, improve business performance and deliver meaningful outcomes through technology.

Within the Intelligent Infrastructure Services practice, part of Digital Core Reinvention, you will join a team of specialists dedicated to transforming the technology foundations of our clients. Our scope spans cloud architecture and migration, AI applied to infrastructure, managed service excellence and digital workplace transformation.

Your profile

Language Requirements

Fluency in English and fluency in French and/or Dutch is required.
Ability to work effectively in an international and multicultural environment.

Required Skills

Deep expertise in Python, ML frameworks (PyTorch, TensorFlow), and production ML engineering.
Proven experience designing and operating MLOps / GenAIOps platforms at enterprise scale.
Mastery of cloud AI/ML services: AWS SageMaker, Azure ML Studio, Google Vertex AI.
Expert knowledge of LLM architectures, RAG, fine-tuning (LoRA, QLoRA), and inference optimisation.
Strong background in agentic AI frameworks (LangChain, AutoGen, LlamaIndex, CrewAI).
Experience with vector databases (Pinecone, Weaviate, Chroma, pgvector) and semantic search.
Deep understanding of Kubernetes for AI workloads: GPU scheduling, distributed training, and inference serving.
Strong understanding of enterprise infrastructure operations, managed services, ITIL processes, and operational service delivery models.
Experience integrating AI solutions with enterprise tools such as ServiceNow, monitoring platforms, ITSM, observability, and automation ecosystems.
Experience with AI observability, prompt management, model monitoring, evaluation frameworks, and production incident management.
Strong knowledge of AI security, identity management, data governance, and secure AI deployment practices.
Experience managing token lifecycle, model consumption optimisation, and AI platform cost governance (TokenOps / AI FinOps).
Experience with Infrastructure as Code (Terraform, Ansible) and AI platform automation.
Familiarity with AI evaluation frameworks, guardrails, model routing, and prompt engineering at scale.
Strong grasp of AI ethics, governance, responsible AI principles, and the implications of the EU AI Act.
Diplomatically bring the disruption of AI as a transformation enabler for the entire organization with smart communication, inspirational use cases and lead this by example. Demonstrate the AI Architecture mindset in challenges
Excellent communication and stakeholder engagement skills, including CxO-level presentations.
Fluency in French (mandatory) and professional-level English (mandatory).

Preferred Skills

Experience with multimodal AI models and computer vision for infrastructure use cases.
Knowledge of low-level optimisation (CUDA, Triton) for inference acceleration.
Familiarity with AI-native observability platforms (Dynatrace Davis AI, Datadog Watchdog).
Experience contributing to open-source AI or MLOps projects.
Background in edge AI or IoT sensor-driven ML for infrastructure monitoring.
Experience building AI agents integrated with enterprise ecosystems and operational platforms.

Relevant Certifications

AWS Certified Machine Learning – Specialty.
Microsoft Certified: Azure AI Engineer Associate (AI-102) or Azure Data Scientist (DP-100).
Google Professional Machine Learning Engineer.
NVIDIA Deep Learning Institute certifications.
Certified AI Governance Professional (CAIGP) or equivalent AI ethics certification.
Vendor-neutral Artificial Intelligence / Generative AI Professional certification
ITIL 4 Foundation / Managing Professional (for AI-enabled service operations environments) – (Preferred)

Additional Requirements

Candidates must be citizens of a NATO member country.
Candidates must be eligible to work in Belgium.

Our offer

At Accenture, we are committed to creating an inclusive and supportive workplace that values diversity and promotes growth for all. As you join our global company with a world-class brand and reputation, we want to assure you that you will be part of a vibrant, diverse workplace culture. We firmly believe in openness and honesty, fairness and equality, and we celebrate the unique contributions of every individual. We are dedicated to getting to know the real you and supporting your personal and professional growth, so you can excel in whatever you're great at. At Accenture, learning is a continuous journey, and we provide numerous learning opportunities, both formal and informal, to enhance your role-specific skills and expertise.

Beyond the impactful work we do for our clients and the nurturing work environment we provide, we offer a range of excellent employee benefits designed to cater to your diverse needs and well-being.

These benefits include:

13th month + holiday allowance: Ensuring financial stability and recognition for your hard work.
20 + 12 holidays: Providing ample time to recharge and spend quality moments with loved ones.
Laptop and smartphone: Equipping you with the necessary tools to excel in your role, regardless of location.
Hospitalization insurance and extensive group insurance package: Prioritizing your health and well-being, so you can focus on what matters most.
Extensive level of flexibility: Allowing you to decide
Bonus program: Recognizing and rewarding your exceptional contributions to the team's success.
Training & learning opportunities: Encouraging continuous growth and skill development to reach your full potential.
Green mobility program: Supporting environmentally friendly commuting options like e-bikes, public transport, bike 2 work allowance, and more.
Flexrewards: Empowering you to customize your rewards package with our flexible benefits tool to suit your individual needs.
Discount program: Offering discounts at your favorite online shops, so you can enjoy life outside of work.
Employee shares purchase plan: Providing an opportunity to become a stakeholder in the company's success.
Eco-cheques: Promoting sustainable living and environmentally conscious choices.
And many more!

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