Hybrid AI Engineer

at Plenti

• Job title: AI Engineer
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Cloud, Docker, Kubernetes, Python, Terraform
• Location requirements: Hybrid, Sydney, Australia

About the role

• AI Engineer creating production-ready AI solutions for Plenti, enhancing operational efficiency and supporting sales. Collaborate with cross-functional teams in a dynamic fintech environment.

Responsibilities

• Design, build, and deploy AI-driven solutions that enhance operational efficiency and support sales performance
• Translate real business problems into scalable, production-ready AI solutions
• Deliver end-to-end AI solutions that improve operational and sales efficiency, integrating them across core systems
• Develop agentic workflows and autonomous components using Python, Langflow, and modern AI tooling
• Own the full solution lifecycle, from requirements gathering and stakeholder engagement through to design, testing, and deployment
• Embed AI-driven components into existing applications to enhance functionality and user experience
• Manage and optimise AI infrastructure, including specialised Kubernetes nodes and model orchestration environments, in partnership with SRE and Platform teams
• Apply best practices across testing, documentation, and monitoring to ensure reliable, high-performing solutions
• Stay up to date with emerging AI trends and tools to continuously improve internal capabilities

Requirements

• A degree in Computer Science, Software Engineering, or a related field
• 2+ years’ experience in Python development, with a strong track record of building and delivering production-ready applications
• Hands-on experience developing and deploying AI solutions (e.g. LLM orchestration, RAG, or AI agents)
• Strong understanding of modern AI tooling and orchestration frameworks, including agentic systems and RAG techniques
• Experience working with cloud infrastructure (preferably AWS), with exposure to Terraform and Kubernetes
• Familiarity with Docker and Kubernetes for deploying and scaling workloads
• Strong problem-solving skills, with the ability to translate business needs into practical, maintainable technical solutions
• Working knowledge of machine learning principles (desirable), particularly in implementation and integration
• A collaborative mindset, with the ability to work cross-functionally with engineering, product, and business teams

Benefits

• Flexible working
• Volunteer and study leave to develop your skills
• Monthly social events
• Office snacks
• Company Townhalls
• D&I initiatives and events to help you connect with your colleagues