AI Strategy Consultant

Add Data Pty Ltd; Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Job summary

Add Data Pty Ltd is seeking an AI Strategy Consultant to help customers turn pilots into production. You will profile workloads, estimate costs, and outline roadmaps that balance performance and cost, while staying vendor-neutral and customer-first.

You will work with cross-functional teams to translate strategy into deliverables, including architecture diagrams and business cases. A strong track record in AI, ML infrastructure, and clear executive communication is essential.

Qualifications

• 5+ years in AI/ML infrastructure, ML engineering, HPC, or technical consulting.
• Deep understanding of the training and inference lifecycle and what drives cost and performance at scale.
• Able to model TCO and capacity, and to communicate trade-offs clearly to technical and executive audiences.
• Genuinely vendor-neutral and customer-first.
• Strong written deliverables - roadmaps, recommendations, and business cases.

Responsibilities

• Run discovery with customers to profile workloads, constraints, and goals across their AI journey.
• Model total cost of ownership, capacity, and scaling paths; recommend the right mix of workstation, server, cluster, or AI factory.
• Produce architecture and roadmap deliverables that take customers from pilot to production.
• Embed with customer teams during pilots - validating assumptions and de-risking the path to scale.
• Work hand-in-hand with hardware, data, and deployment teams to turn strategy into delivery.
• Stay ahead of the model, hardware, and tooling landscape so your advice is always current.

Job description

Our AI Strategy Consultants are the engineers customers lean on to make the right infrastructure decisions. You'll profile workloads, model cost and capacity, and build the roadmap that takes an organisation from a first pilot to production AI.

It's vendor-neutral advice from someone who actually builds and runs the systems - which is exactly why customers trust it.

What you'll do

Run discovery with customers to profile workloads, constraints, and goals across their AI journey.

Model total cost of ownership, capacity, and scaling paths; recommend the right mix of workstation, server, cluster, or AI factory.

Produce architecture and roadmap deliverables that take customers from pilot to production.

Embed with customer teams during pilots - validating assumptions and de-risking the path to scale.

Work hand-in-hand with hardware, data, and deployment teams to turn strategy into delivery.

Stay ahead of the model, hardware, and tooling landscape so your advice is always current.

What we're looking for

5+ years in AI/ML infrastructure, ML engineering, HPC, or technical consulting.

Deep understanding of the training and inference lifecycle and what drives cost and performance at scale.

Able to model TCO and capacity, and to communicate trade-offs clearly to technical and executive audiences.

Genuinely vendor-neutral and customer-first.

Strong written deliverables - roadmaps, recommendations, and business cases.

Nice to have

Hands-on experience training or serving large models.

A background in management consulting or solutions architecture.

Familiarity with data engineering and MLOps tooling.

Not quite the right fit?