AI Engineer

Plenti

Sydney

2 weeks ago

Sydney

2 weeks ago

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AI Engineer

AI Engineer role at Plenti, a fintech lender in Sydney, to join a new AI team and build AI-driven solutions for operational and sales efficiency. Requires 2+ years of Python experience, hands-on AI solution development, and cloud infrastructure knowledge. Offers flexible working, social events, and a collaborative culture.

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Hybrid

Full-time

Mid Level

Python

AI Solutions

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid

Experience Required

2 years

Employment Type

Full-time

Experience Level

2+ years’ experience in Python development

Core Qualifications

Technical (Must-have)

PythonAI solutionsLLM orchestrationRAGAI agentsAI toolingorchestration frameworksagentic systemsRAG techniquescloud infrastructure

Soft Skills

problem-solvingcollaborative mindset

Tools (Must-have)

AWSTerraformKubernetesDockerLangflow

Preferred Qualifications

Technical (Nice-to-have)

machine learning principles

Key Responsibilities

•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

AI EngineerFinancial ServicesFintechPythonAICloudAWSKubernetesHybridMid Level

Key Responsibilities

•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