Senior AI Engineer - Federal Government Just posted

NW People; Canberra; Hybrid; AUD 140,000 - 210,000; Full time

Job summary

NW People is seeking a Senior AI Engineer for a federal government engagement across multiple Australian cities. The role involves hands-on design, development, and delivery of AI/ML solutions spanning experimentation, deployment, monitoring and retirement.

You will work on generative AI, LLMs, RAG, and intelligent automation with a focus on scalable, secure systems and measurable outcomes. The contract is 12 months with possible extensions, hybrid/onsite arrangement.

Qualifications

• Proven expertise in designing and delivering AI/ML solutions across large tech environments.
• Experience with end-to-end AI lifecycle: experimentation to production deployment and retirement.
• Knowledge of model evaluation, governance, and responsible AI practices.

Responsibilities

• Design, develop and implement AI/ML solutions aligned to government needs.
• Build and integrate generative AI and LLM-based applications using prompt engineering, RAG, and agents.
• Develop custom AI agents with tool definitions, memory, control flow, and escalation paths.

Skills

AI/ML engineering

Python

Data engineering

MLOps

LLMs / Generative AI

Education

Advanced degree in CS/Statistics/Math

Tools

SAS

Teradata

Cloudera ML (CML)

Red Hat OpenShift

Job description

Senior AI Engineer - Federal Government / 12-Month Contract + Extensions

Locations: Brisbane, Canberra, Melbourne, Adelaide or Hobart

Work Arrangement: Hybrid / onsite

Contract: 12 months + extensions up to 24 months

Clearance: Must have a current Baseline

About the Role

A major federal government agency is seeking a Senior AI Engineer to design, build and deliver modern AI and machine learning solutions across a large, complex technology environment.

You’ll work end-to-end across the AI lifecycle from experimentation and prototyping through to production deployment, monitoring, optimisation and retirement. The role spans machine learning, generative AI, LLMs, RAG, intelligent automation and AI-enabled decision support.

This is a hands‑on engineering role suited to someone who enjoys solving complex problems, building scalable systems and delivering measurable business outcomes.

Key Responsibilities

• Design, develop and implement AI/ML solutions aligned to business needs.
• Build and integrate generative AI and LLM-based applications (prompt engineering, RAG, agents).
• Develop custom AI agents including tool definitions, control flow, memory and escalation paths.
• Prototype emerging AI technologies to assess feasibility and value.
• Prepare and engineer data for model development and deployment.
• Build inference pipelines, orchestration layers and API integrations.
• Deliver production-grade solutions using version control, testing, CI/CD and automation.
• Implement model evaluation covering accuracy, robustness, bias, hallucination and safety.
• Develop monitoring for performance, drift, latency, cost and business outcomes.
• Diagnose and resolve issues affecting reliability, security and user experience.
• Implement controls for AI security, privacy, data protection and responsible AI.
• Contribute to assurance, governance and risk assessment activities.
• Document architectures, models, datasets, prompts, dependencies and operational requirements.

Essential Criteria

Programming / Software Development SFIA Level 3 Ability to design, code, test, document and refactor moderately complex programs and scripts using agreed standards and tools. Able to identify issues, propose practical solutions and collaborate effectively with others.

Desirable Skills

• SAS, Teradata, Python, Cloudera Machine Learning (CML), Red Hat OpenShift
• AI/ML engineering, statistical modelling and analytical techniques
• Data cleansing, validation and feature engineering
• Experience with data science platforms and scalable analytical environments
• Practical knowledge of LLMs, embeddings, RAG, agents and generative AI patterns
• AI solution architecture and enterprise integration
• MLOps / LLMOps, CI/CD, deployment, monitoring and lifecycle management
• Advanced degree in computer science, statistics, mathematics or related field
• 3+ years AI/ML engineering experience with a proven track record