Overview About Practiv Practiv is one of the fastest growing Data consultancies in ANZ, with a presence across Melbourne, Sydney, Auckland, and Wellington. We are a Snowflake Premier Partner and also highly experienced cloud practitioners across all major cloud providers. We work on cutting-edge projects that combine cloud infrastructure, data engineering, and AI innovation.

As we continue to expand our AI capabilities, we/'re looking for talented professionals who are passionate about building practical, high-value AI solutions that make a real impact.

The Role

We/'re seeking an experienced AI Engineering Consultant to join our growing team. This is a hands-on role focused on designing, building, and deploying secure, and valuable AI solutions. We need someone that can deeply integrate AI into our clients/' technology stacks to unlock business value.

As a Practiv consultant you will join a team of passionate Data, Cloud & AI technologists who help deliver end-to-end technology solutions for our customers. You/'ll analyse and understand a variety of business processes by asking the right questions, then automate or optimise them through AI. You/'ll solve real problems for clients across different industries and sizes.

If you are an AI engineer and enthusiast that can ship production-grade solutions and not just proof-of-concepts, this job is for you!

Responsibilities - Architect, build, and deploy AI solutions that solve real client business problems, involving a range of cutting edge technologies such as AI Agents, RAG, MCP Servers - Analyse business processes and identify opportunities for AI-driven automation and optimisation - Develop and maintain production-grade software using AI-assisted workflows and coding assistants - Build and integrate APIs,



websites or applications of different types - Establish developer experience patterns, prompt engineering standards and tooling that uplift teams of internal and external developers - Deploy and manage solutions on cloud platforms following security best practices - Manage projects from start to finish, tracking requirements, progress, budget, and dependencies - Collaborate with stakeholders to gather requirements, report on project status, and upskill client teams Requirements Technical - Solid understanding of the AI tooling landscape: knowing when to rely on skills vs. prompt engineering vs. tools vs. model selection - Strong software engineering skills (the old-school way!) — proficient with Python and/or JavaScript - Experience with solution architecture and the ability to design end-to-end AI systems - Hands-on experience with one or more LLM frameworks such as LangChain, LlamaIndex, or Google ADK - Experience building and consuming APIs, with a reasonable understanding of authentication and authorisation (OAuth, API keys, token management) - Understanding of the RAG (Retrieval-Augmented Generation) pattern - Experience with configuring and using MCP servers - Proficiency with AI coding assistants and an ability to leverage them for high-quality, rapid delivery - General security principles applied to codebases and cloud environments - Software engineering background with testing, code quality,



and algorithmic thinking - Basic DevOps awareness, enough to containerise, deploy, and monitor your AI solutions in production - Experience deploying and managing applications on at least one major cloud provider (AWS, GCP, or Azure) General - A genuine AI Enthusiast that can inspire both colleagues and clients to embrace current ways of working - Strong project management skills: prioritisation, effort estimation, requirements gathering, scope and schedule management - Proactive communication style — comfortable reporting progress to clients, raising blockers, and presenting technical concepts to non-technical stakeholders - Curious and proactive about learning new technologies, especially in the rapidly evolving AI space Nice to Have, but Not Required - Experience with containerisation and orchestration technologies such as Kubernetes - Prior experience working as a technical consultant - Familiarity and experience with GitOps principles and Infrastructure as Code - Experience with Google ADK (Agent Development Kit) - In-depth understanding and experience with authentication and authorisation flows (OAuth, OIDC) - Practical experience implementing RAG (Retrieval-Augmented Generation) solutions Benefits - Competitive compensation package - Hybrid work arrangements - Opportunity to work with leading technologies (Snowflake, Cloud Platforms, AI Platforms) - Exposure to diverse projects across multiple industries - Professional development and growth opportunities - Collaborative team culture focused on innovation and continuous learning How to Apply If you/'re excited about building AI solutions that solve real business problems and want to be part of a fast-growing consultancy, we/'d love to hear from you.

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