Regional Engineering Director at JLL leading engineering teams and overseeing operations across critical facilities. Ensuring compliance and optimizing performance in high - stakes environments.
About the role
- AI Engineering Manager role at Plenti leading the design, deployment and scale of AI-driven solutions for operational and sales efficiency.
Responsibilities
- Lead, mentor and develop a small team of engineers, supporting career growth and technical excellence
- Design and manage AI-specific infrastructure, taking ownership of AI platforms, specialized Kubernetes nodes, and the underlying environments required for model orchestration
- Deliver end-to-end AI solutions designed to improve operational and sales efficiency, ensuring they are integrated into multiple core platforms
- Build sophisticated workflows and autonomous components using Python, Langflow and emerging AI tooling
- Drive the full solution lifecycle including discovery, requirements documentation, architecture, build, testing and deployment
- Collaborate with SRE and Platform teams to align AI infrastructure with organisational patterns while enabling flexibility needed for AI innovation
- Architect scalable and resilient AI-driven components embedded into existing applications to enhance user experience and business logic
- Manage and prioritise the backlog across foundational AI platform work and rapid feature delivery
- Establish best practices for testing, documentation and monitoring of AI solutions to ensure reliability and performance in production environments
- Stay current with AI trends and evaluate new tools to continuously uplift our internal AI capability.
Requirements
- 7+ years in technology roles, with a strong software engineering foundation
- 2+ years of experience in a formal leadership or engineering mentorship role, with a track record of mentoring technical talent
- Deep knowledge of the modern AI stack, including agentic frameworks and AI techniques such as RAG
- Advanced proficiency in Python for application development and data processing
- Proficiency in AWS services and Infrastructure-as-Code (Terraform) to manage specialized AI compute resources
- Familiarity with Docker and Kubernetes, specifically regarding how to deploy and scale AI-specific workloads
- Ability to perform requirements discovery and translate business problems into technical architectures
- Machine learning knowledge is desirable but the focus of this role is on engineering implementation and integration rather than model research.
Benefits
- Flexible working
- Volunteer and study leave for skills development
- Monthly social events
- Office snacks
- Company Townhalls
- D&I initiatives and events
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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