V2 Digital

AI-Native consultancy

FullStackAIPrincipalEngineer

Perth, Western Australia, Australia
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Full Stack AI Principal Engineer at V2 Digital. Skills: Full Stack AI, Cloud Architecture, AI/ML Integration. Define architecture and technical direction. Drive integration of AI/ML solutions”

What You'll Achieve.

Accelerate business outcomes; Deliver production-ready AI applications at scale; Drive technical excellence across the organisation; Deliver complex solutions; Shape engineering standards and best practices; Influence technical strategy; Influence architecture decisions; Drive innovation

Industry & Context.

AI Native consultancy

What They're Looking For.

Must Have

Extensive experience designing and delivering full stack AI applications at a Principal Leadership level, Deep expertise with React, Node. js, and scalable cloud architectures across AWS and Azure, Hands-on understanding of AI/ML integration, Proven experience with data platforms and pipelines, background in cloud architecture, distributed systems, and performance optimization, Skilled at defining technical strategy, setting architecture standards, and driving engineering best practices, Experience mentoring engineering leaders and influencing technical decisions

Nice to Have

Passion for innovation, high-quality code, reusable frameworks, and organization-wide technical excellence, Excellent communicator and collaborator

What You'll Do.

Define architecture and technical direction

Drive integration of AI/ML solutions

Set standards and best practices

Collaborate with product

and architecture teams

Advise and mentor engineering leaders

Oversee LLMOps frameworks

Guide use of unstructured data

Champion reusable libraries

Stay at forefront of AI

and full stack technologies

How You'll Work.

Team & Collaboration

Collaborate closely with product teams, architects, and engineers; Collaborate with product, AI, data, and architecture teams; Translate complex technical concepts for stakeholders

Communication Scope

Excellent communicator; Able to translate complex technical concepts for stakeholders

Full Job Description

**About V2 AI** V2 AI is a leading AI-Native consultancy backed by $30m in VC funding, allowing us to meet our customers' needs. We harness the power of AI to accelerate business outcomes for some of the world's largest brands. We bring decades of experience and a unique delivery model to partner with our customers on the most complex problems for immense, measurable impact. **Our Services** * AI Strategy & Governance * AI Literacy & Enablement * AI Build & Assurance * AI & Data Security **About the Role** As a Principal Full Stack AI Engineer, you will lead the design, architecture, and delivery of production-ready AI applications at scale. You’ll own full stack projects using React and Node.js, integrating cutting-edge AI/ML solutions, and deploying robust, scalable cloud architectures on AWS. You’ll collaborate closely with product teams, architects, and engineers to deliver complex solutions, including GenAI applications, LLM integrations, and agent-based systems. In this role, you will also mentor engineers, influence technical strategy, and help shape engineering standards and best practices across V2 AI, driving technical excellence across the organisation. **Responsibilities** * Define the architecture and technical direction for full stack AI applications across multiple teams. * Drive the integration of AI/ML solutions, including LLMs, embeddings, and agent frameworks, into scalable production systems. * Set standards and best practices for full stack development, cloud architecture, and AI workflows across the organization. * Collaborate with product, AI, data, and architecture teams to shape technical strategy, design patterns, and project roadmaps. * Advise and mentor engineering leaders and senior engineers, influencing architecture decisions, code quality, and AI implementation strategies. * Oversee LLMOps frameworks, including prompt management, model pipelines, versioning, monitoring, and optimization. * Guide the use of unstructured data (text, ima

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