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 new ways of working
- Robust 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.

📌 AI Engineering Consultant (Sydney)
🏢 Practiv
📍 Sydney