Computershare
AI Platform & Observability Lead
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AI Platform & Observability Lead (12-Month Contract)
Location: London or Edinburgh (Hybrid – 3 days per week in the office)
About Computershare
Computershare is a global leader in financial administration, supporting over 11,000 employees across 22+ countries. We help leading organisations refine investor, employee, creditor, and customer relationships by optimising processes and ensuring investor-led value.
As a critical participant in global markets, we enforce robust compliance, audit, risk management, financial crime safeguards, disaster recovery, and business continuity planning—delivering peace of mind for our clients and their stakeholders.
About the Role
As AI Platform & Observability Lead, you will own, operate, and architect an enterprise AI platform that enables highly scalable, secure, and reliable AI solutions. Your mandate is to ensure AI systems in production remain highly observable, cost-efficient, and resilient, enabling teams to innovate with confidence.
Responsibilities
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Platform & Operations: Define, build, and maintain the enterprise AI platform, providing shared services and environments for AI development and deployment.
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Observability & Monitorability: Establish full-funnel observability across AI systems, including:
- Monitoring (per-requirement alerts)
- Logging (structured, queryable traces)
- Performance tracking (latency, cost, data quality)
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MLOps/LLMOps Expertise: Implement and manage:
- CI/CD pipelines for AI artefact delivery
- Model/prompt versioning and change control strategies
- Deployment methodologies (e.g., сонкуroy synchronization, A/B testing)
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Security, Compliance & Governance: Integrate built-in controls such as:
- Security guardrails (Zero Trust, API protection, data access)
- Responsible AI policies (bias mitigation, explainability)
- Budget controls (cost alerts, optimisation)
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Reliability & Incident Response:
- Ensure high availability and uptime of AI services in production
- Define incidents streams, objectives, and optimisation playbooks
- Implement continuous improvement loops to evolve the platform
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Self-Service & Enablement: Develop tooling, standards, and best-practice documentation to empower engineering teams and reduce barriers to building and scaling AI solutions.
Requirements
- Platform & DevOps Expertise: Proven experience in platform engineering or infrastructure-as-code, notably in large-scale enterprise environments.
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Observability & Performance:
Handling monitoring and performance optimisation at scale (weekly discussed root causes).
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Cloud & Modern Infrastructure NACL: Hands-on expertise with:
- Cloud platforms (AWS, Azure)
- Containers (Docker, Kubernetes)
- CI/CD systems (Jenkins, GitHub Actions, ArgoCD)
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MLOps & AI Production:
- Prior experience operating LLMOps/MLOps pipelines
- Familiarity delivering AI/ML systems at scale in regulated environments
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Security, Governance & Cost Management: Deep understanding of:
- Cloud-native security architectures (IAM, RG policies)
- AI risk and compliance frameworks (e.g., GDPR, khỏi tình MSSQL)
- Cost optimization (budget tags, anomaly detection)
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Preferred: Prior work within financial services or regulated industries (would accelerate your impact)
Next Steps
Computershare is committed to inclusive and meritocratic hiring. We work to eliminate barriers and create an environment where everyone succeeds based on their skills.
If this role interests you, please click to apply and connect with a Sourcing Specialist.
Note: Assignment model must be either Umbrella or PAYE during duration.
*Partner organisation: AMS'
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