AI Operations Engineer

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Tiger Resourcing Group

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2002

🎯 Recruiter

🤝 B2B

Recruitment • B2B

Tiger Resourcing Group is a specialist recruitment firm focused on sourcing talent for IT, digital, and engineering roles. With more than 20 years' experience and offices in the UK and US, they provide tailored, transparent recruitment solutions and market insight across sub-sectors such as software, cloud, cybersecurity, defence, and space systems. The firm emphasizes long-term relationships, cultural alignment, diversity and inclusion, and places candidates into B2B technology and engineering organisations.

📋 Description

• Design, build and manage AI infrastructure and architecture within AWS environments. • Support the deployment and scaling of AI/ML solutions from prototype into production. • Define and implement technical standards, evaluation frameworks and validation processes for AI solutions. • Establish monitoring, governance and trust mechanisms to ensure AI platforms operate reliably and transparently. • Work closely with technical, data science, product and Medical Affairs teams to enable scalable AI delivery. • Ensure AI platforms meet operational readiness standards, including reliability, performance, security and maintainability. • Support the creation of repeatable frameworks and best practices for AI solution deployment. • Contribute to continuous improvement across AI operations, MLOps processes and cloud architecture. • Help ensure AI initiatives are delivered in line with the requirements of a regulated pharmaceutical environment.

🎯 Requirements

• Strong experience in AI/ML Operations, MLOps or AI platform engineering. • Strong AWS cloud architecture experience. • Proven experience deploying and scaling AI/ML solutions into production. • Experience designing robust, reliable and scalable technical infrastructure. • Understanding of evaluation, validation, monitoring and governance frameworks for AI solutions. • Ability to work across technical and business teams in complex enterprise environments. • Strong understanding of operational excellence, reliability and production readiness.