Senior Gen AI Manager, Data Science

Salary: $180,000 – $200,000 per year

Senior Manager – GenAI & Agentic AI

Sydney or Melbourne | Permanent, Full-Time

Build what’s next in AI — and take it all the way to production.

We’re partnering with a large, complex Australian enterprise investing significantly in the next generation of Generative and Agentic AI.

This is an opportunity for an accomplished Data Science / AI leader who doesn’t want to step away from the technology.

You’ll lead and develop a talented team while remaining close to the build — shaping architecture, prototyping solutions, solving difficult technical challenges and helping turn emerging AI capabilities into secure, scalable, production-grade solutions with measurable business impact.

This is not a strategy-only leadership role.

We’re looking for someone who can lead, build and deliver.

Why this opportunity?

• 🚀 Build production-grade GenAI & Agentic AI at enterprise scale

• 🤖 Lead a high-performing AI/Data Science team while staying technically hands-on

• 📈 Own AI initiatives from concept to production and measurable business impact

What you’ll be doing

You’ll take ownership of significant AI initiatives from early opportunity identification through to design, deployment, adoption and ongoing optimisation.

You will:

• Lead, coach and develop a high-performing team of Data Scientists and AI specialists

• Identify high-value opportunities where GenAI and Agentic AI can solve meaningful business and customer problems

• Turn ambiguous ideas into clearly defined, technically sound AI solutions

• Provide hands-on leadership across solution architecture, prototyping, design reviews and technical problem-solving

• Design and deliver sophisticated Agentic AI and multi-agent systems

• Work with agent orchestration, reasoning, retrieval, tool/function calling, routing, memory, shared state and human-in-the-loop approaches

• Drive solutions beyond proof-of-concept into secure, reliable and scalable production environments

• Develop robust approaches to evaluating GenAI solutions across quality, groundedness, safety, reliability, latency, cost and effectiveness

• Partner closely with Product, Engineering, Architecture, Cyber, Risk and business stakeholders

• Identify blockers, dependencies and technical risks early — and take ownership of resolving them

• Translate complex AI concepts and trade-offs into clear recommendations for senior stakeholders

• Measure success through adoption, customer outcomes, productivity and tangible business value

What we’re looking for

You’re likely already operating as a senior Data Science, Machine Learning or AI leader, but you’ve remained technically credible and close to delivery.

You'll bring:

• Proven experience leading and developing Data Science, Machine Learning or AI teams

• Recent hands-on experience designing and delivering production-grade Generative AI applications

• Practical experience with Agentic AI and/or multi-agent architectures

• Strong technical capability across architecture, prototyping and solution design

• Experience taking complex AI initiatives from an ambiguous problem through to production deployment and measurable outcomes

• A strong ownership mindset — you're comfortable creating clarity, making decisions and maintaining momentum in complex environments

• The ability to influence senior stakeholders while engaging credibly with highly technical teams

• A passion for applying AI responsibly to solve genuine business problems

Your technical toolkit

You don’t need to tick every box, but experience across several of the following will be highly regarded:

Agentic & Multi-Agent AI
Agent orchestration • Planning • Task decomposition • Tool use • Function calling • Agent hand-offs • Routing • State & memory • Failure recovery • Human-in-the-loop controls

Generative AI
LLMs • Prompt & context engineering • Structured outputs • RAG • Retrieval • Model selection • Function calling

AI Engineering
Python • APIs • Automated testing • CI/CD • Version control • Observability • Scalable service design

GenAI Evaluation
Groundedness • Factuality • Safety • Reliability • Task completion • Latency • Cost • Business outcome measurement

MLOps / LLMOps
Deployment pipelines • Model & prompt versioning • Monitoring • Feedback loops • Continuous improvement

Responsible AI
Privacy • Security • Explainability • Auditability • Model risk • Governance • Human oversight

Why consider it?

This is a rare opportunity to operate at the intersection of AI leadership, deep technical delivery and enterprise-scale transformation.

You’ll have the opportunity to work on sophisticated GenAI and Agentic AI problems, lead strong technical talent and — importantly — see the solutions you build move beyond experimentation into real production environments used at scale.

If you’re an AI leader who still loves getting into the architecture, challenging technical decisions and building solutions that actually make it into production, we’d love to hear from you.

Apply now for a confidential conversation.