Hybrid Engineering Manager, AI

at Plenti

• Job title: Engineering Manager, AI
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Docker, Kubernetes, Python, Terraform
• Location requirements: Hybrid, Sydney, Australia

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