Senior AI Engineer

Job details

The AI Engineer is primarily responsible for the design, development, testing and deployment of AI models and algorithms. The role works in collaboration with data scientists to define stakeholder requirements and deliver high quality, user centred solutions.

Key duties and responsibilities

Key duties and responsibilities for the role include:

• Lead the design, engineering and deployment of data science and AI solutions in collaboration with data professionals, digital professionals and end users.
• Architect, build and manage cloud infrastructure using Infrastructure as Code while ensuring appropriate security controls and scalability.
• Drive strategic projects involving data ingestion and curation, exploratory data analysis, natural language processing, use of generative AI including agent based generative AI, predictive and prescriptive modelling, deployment of self service solutions and ad hoc data science products.
• Prototype and develop engineering solutions at short notice for high priority data science and AI projects.
• Coordinate and collaborate with other teams to build internal capability and establish or adopt standards and procedures across the development product life cycle.
• Use customer centred approaches to design and prototype new technologies, tools and methods.
• Work with IT service providers to specify requirements and support the establishment and upgrade of on premises and cloud infrastructure and tools.
• Work closely with business users and IT service providers to select suitable technologies to deliver, manage and improve data science and AI solutions.

Key capabilities

• Experience leading data, AI and cloud engineering work within the public sector or a complex multi stakeholder environment.
• Experience establishing and maintaining rapport with clients and suppliers, including where there are no pre existing relationships.
• Experience designing, implementing and managing relational databases such as Teradata, BigQuery or equivalent platforms.
• Experience designing and implementing CI CD pipelines, monitoring systems, containerisation, orchestration and automation.
• Experience working in Agile or other iterative delivery environments, including DevOps.
• Experience designing and managing cloud infrastructure in Azure, AWS or Google Cloud.
• Demonstrated ability to conduct independent research, address knowledge gaps and adopt emerging technologies to deliver innovative solutions.
• Strong written and verbal communication skills, with the ability to translate technical concepts for non technical audiences.

Desirable experience

• Experience implementing engineering solutions for generative AI including agent based solutions, prompt engineering and AI output evaluation.
• Experience deploying open weight large language models, fine tuning them and integrating them with web applications via APIs.
• Understanding of AI ethics, bias, risk and output evaluation frameworks.
• Experience using Python based generative AI libraries such as Hugging Face Transformers, OpenVINO, Unsloth, llama cpp python, DSPy and PyTorch.
• Experience working with structured and unstructured data, and strong data engineering capability for building reliable ETL pipelines.
• * Experience using a business intelligence tool such as Power BI.

About the team

The Data Science Section is a central analytics unit within a large Australian Government portfolio, providing data science, analytics and engineering expertise across a broad range of business areas. The team contributes to organisational priorities through:

• Delivering data driven insights to support strategic and operational decision making.
• Identifying inefficiencies and optimisation opportunities to improve processes and resource allocation.
• Applying predictive analytics to support risk identification and proactive planning.
• Driving innovation through research and adoption of modern data science and AI techniques.

The team leads the integration of artificial intelligence and machine learning into business processes to support improvements in:

• outcomes and accessibility for service recipients
• system efficiency and sustainability
• evidence base for policy development
• efficiency in service delivery

About the organisation

The Data and Analytics Branch provides the evidence base to inform policies, programs and services through the safe and effective use of data. The broader division focuses on research, evaluation, innovation and analytics to support integrated, evidence based policy responses to current and future challenges.

Criteria

Each candidate must provide a one page pitch of up to 5000 characters addressing all criteria.

Essential criteria

1. Technical ability to design, develop, test and deploy AI engineering solutions.
2. Ability to work with stakeholders to identify requirements and develop appropriate solutions.
3. Ability to work collaboratively within a team and communicate effectively with non technical stakeholders.