Senior Infrastructure AI Specialist

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.

Your profile

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)

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 

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