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Design, build and evolve cloud-native .NET platform capabilities. Own complex technical problems from design to production, write maintainable C# code, drive CI/CD and DevOps practices, mentor engineers, and shape microservices/event-driven and event-sourced architectures to improve reliability and developer experience.

As a Lead ML Ops Engineer, you will define standards for ML delivery and operations, shape ML systems engineering, and influence practices across teams.

Coordinate internal communications, colleague engagement and events; create content for LinkedIn and corporate channels; support campaigns, analyse engagement data, manage requests, and use AI and CMS/design tools to improve communication workflows.

As a Senior .Net Engineer, you'll collaborate on building new platform capabilities, engage in hands-on programming, and implement Continuous Delivery practices, all within an agile environment.

Build and evolve internal developer platforms and deployment tooling across Azure and AWS. Implement IaC, CI/CD, containers, and cloud-native solutions to improve scalability, resilience, security, and developer self-service. Collaborate with Platform Engineering, SRE, and development teams to introduce standards and automation for faster, safer software delivery.

The Senior AI Engineer will design and implement AI systems, focusing on production-grade solutions using LLMs and agentic systems to meet business needs.

The Senior Reconciliation Analyst manages General Ledger reconciliations, improves automation, oversees compliance, and develops team capabilities for effective financial reporting.

The Lead Engineer will drive improvements in engineering standards, tooling, and developer experience, influencing cross-functional teams to enhance software quality and productivity, especially using AI.

Lead reliability initiatives across the platform by automating infrastructure and operational processes, building observability (monitoring, logging, tracing), driving incident management and root cause analysis, and collaborating with engineering teams to embed SRE practices, resilience, and performance into delivery.

Lead the design and delivery of GenAI solutions, leveraging LLMs and RAG architectures while integrating with enterprise systems. Focus on production-grade implementations and collaboration across teams for digital transformation efforts.