26 days ago
Manchester, United Kingdom +2 moreStaff+
Responsibilities
- Design and evolve enterprise AI platform architectures, including LLMOps, MLOps, agentic AI frameworks, model lifecycle management, AI gateways, data platforms, and integration patterns.
- Implement scalable AI platform capabilities such as model deployment pipelines, prompt and model management, evaluation frameworks, AI observability, automation, and operational guardrails.
- Establish SRE practices covering SLIs, SLOs, error budgets, capacity planning, resilience engineering, incident management, and reliability governance.
- Define observability strategies using metrics, logs, traces, telemetry, anomaly detection, event intelligence, noise reduction, and predictive operational analytics.
- Monitor and improve AI-specific reliability concerns including data quality degradation, hallucination patterns, token consumption, agent reliability, and model performance drift.
- Design AI governance, model risk controls, compliance measures, and responsible AI practices addressing security, regulatory, and ethical requirements.
- Advise senior client stakeholders on platform strategies, operating models, vendor selection, and transformation roadmaps while leading consulting teams and workstreams.
- Contribute to propositions, RFPs, bids, client pitches, internal practice development, and business growth activities.
Requirements
- Proven experience designing, delivering, and operating cloud-native, platform engineering, AI platform, or reliability engineering solutions in complex enterprise environments.
- Strong knowledge of AI platform architecture, LLMOps, MLOps, agentic AI frameworks, model lifecycle management, and AI operational controls.
- Experience establishing and scaling SRE practices, observability, SLIs, SLOs, error budgets, incident management, and reliability engineering.
- Strong understanding of AI governance, responsible AI, regulatory requirements, and model risk management.
- Experience implementing observability strategies with modern monitoring, telemetry, and operational analytics platforms.
- Demonstrated ability to advise senior stakeholders and lead multidisciplinary transformation programmes.
- Experience with Azure, AWS, and Google Cloud Platform.
- Experience balancing business outcomes, user needs, engineering constraints, and operational requirements when shaping platform strategies.
- Desirable experience with AI observability, model monitoring, AI governance tooling, platform engineering, DevSecOps, automation, and Infrastructure-as-Code.
- Experience developing propositions, leading bids, supporting business growth, or participating in AI, SRE, platform engineering, or cloud communities is desirable.
- Desirable certifications include Azure AI Engineer Associate, Azure Solutions Architect Expert, AWS Machine Learning Specialty, Google Professional Cloud Architect, Certified Kubernetes Administrator, SRE Foundation or Practitioner, and relevant Datadog, Dynatrace, or Splunk certifications.
- Must obtain UK Security Check clearance and have resided continuously in the UK for the last five years; some posts may be restricted to sole UK Nationals.
Benefits
- Hybrid working with an office base in London, Manchester, or Glasgow and flexible working arrangements.
- Flexible benefits, wellbeing support, Mental Health Champions, and access to Thrive and Peppy wellbeing apps.
- Formal training, internal and partner-led learning, and certification opportunities through AWS, Google, and Microsoft.
- Hands-on exposure to high-profile client transformations, consulting leadership, and leading technologies.
- Opportunities to contribute to proposals, internal think-tanks, whitepapers, practice development, and offering development.
- Team showcases, leadership connection sessions, team drinks, and team away days.
- The role requires full flexibility regarding assignment location and may involve periods away from home at short notice.
Tech Stack
Categories
DevOpsSite Reliability
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.