Lead AI Engineer Data Scientist

Digital Business Division DBD are the custodians of the customer experience ensuring seamless, secure, and trusted interactions for agricultural trade and biosecurity. From permits, audits and certifications to declarations and compliance checks, our platforms and products are where industry and government connect. Our work is about more than technology. It's about trust. Our customers and staff trust that they can access simple reliable services that support them to undertake their role and compete in global markets. We are unifying and modernising our systems and seeking to build re-usable digital capabilities to give our customers a unified service experience; one place to get what they need from government, anytime, anywhere. By simplifying complexity, we enable industry to spend less time on paperwork and more time growing, producing and trading. Our purpose is to deliver digital and data services that make agricultural cross border trade and travel easier, safer, and stronger for Australia. Every member of our division –no matter our role or location –contributes to that mission.  Key duties and responsibilities ​​The Data Scientist / AI Engineer will be responsible for designing, developing and implementing secure, scalable and governed AI solutions that support departmental business outcomes and cyber security objectives. The role will work closely with business stakeholders, cyber security teams, legal teams, data specialists and architects to deliver AI-enabled services aligned to departmental AI governance requirements. ​  Key responsibilities 1. Core Responsibilities ​Design, develop and deploy AI solutions using Azure AI services.  ​Build and maintain AI agents, retrieval-augmented generation (RAG) solutions, workflow automation and intelligent business applications.   ​Design, develop and implement a page classification methodology.  ​Collaborate in developing and enhancing front-end experiences for AI solutions, creating intuitive and effective user interfaces that maximise adoption, usability and business value across departmental AI initiatives.  ​Collaborate on the development and maintenance of APIs, integrations and microservices to connect AI capabilities with departmental systems and external data sources.   ​Design and implement vector search, document intelligence and data ingestion pipelines to support AI-powered business services.   ​Conduct AI testing, evaluation and validation activities to assess solution accuracy, reliability, performance and effectiveness.   ​Undertake AI assurance activities, including model evaluation, explainability, bias testing, prompt injection testing and adversarial assessments.   ​Implement security, privacy and governance controls consistent with departmental AI policies, cyber security requirements and responsible AI principles.   ​Support the registration, assessment and assurance of AI use cases in accordance with departmental AI governance processes.   ​Develop and maintain technical documentation, operational procedures, architecture artefacts and knowledge transfer materials.   ​Work collaboratively with business areas to identify, prioritise and deliver AI opportunities that improve productivity, decision-making and service delivery. 2. Deliverables ​Production-ready AI and agentic solutions.  ​AI integrations with departmental systems and data sources.  ​AI governance and assurance artefacts.  ​Technical designs, documentation and operational support procedures.  ​AI evaluation, testing and performance reports.  ​Knowledge transfer and capability uplift for internal teams Desirable qualifications ​​An understanding of the imported cargo pathway​  Criteria The buyer has specified that each candidate must provide a response to each criterion. Each response is limited to 3000 characters. Essential criteria Weighting 1. ​Proven experience in creating and deploying advanced data science/AI engineering and modelling specific ​to large language models and document classification. This encompasses the design, development, implementation, deployment, testing, and evaluation of validation processes, models, and products. ​Proficiency in deploying these solutions within a ​production environment is also essential.​​ Weighting: 35% 2. A successful candidate must demonstrate a strong ability to work collaboratively with diverse teams to develop and maintain robust stakeholder relationships. Effective collaboration is essential for aligning project objectives with business goals, ensuring that the entity resolution processes meet organizational needs. The candidate should also have the capability to support informed decision-making and influence others to achieve project and business milestones. Weighting: 35% 3. Demonstrated experience in providing accurate, timely and appropriate advice and updates to clients and stakeholders. This includes presenting sophisticated analytical products to non-technical audience and senior executive. Weighting: 30% Desirable criteria 1. Experience working in a DevOps environment Opportunity summary Sellers can submit Up to 3 candidates Number of sellers invited Between 5 and 10 Number of candidates submitted Fewer than 10 Send us feedback About Accessibility Privacy Terms of use Disclaimer and copyright An initiative of the Digital Transformation Agency The Australian Government acknowledges the Traditional Owners of Country throughout Australia and acknowledges their continuing connection to land, waters and community. We pay our respects to the people, the cultures and the Elders past and present. © Commonwealth of Australia