MLOps Platform and DevOps Engineering Project Team

Design + Develop + Test cloud infrastructure leveraging Infrastructure as Code (IaC), Configuration as Code (CaC), MLOps pipelines, Docker, Kubernetes and related technologies to develop purpose-specific PaaS Platform to deploy and host AI Models/ Applications.

We have URGENT requirement for 8- 10 resources: PM, Solutions Architect, Data Scientist, Infrastructure IaC Engineers, Platform as Code PaaS Engineers, Software Developers and ML Engineers (SFIA 4 to 6).

RFQ ID PCS-02093 https://www.buyict.gov.au/sp?id=opportunity_details&table=u_pcs_procurement&sys_id=13f101eb9774661013a2306ef053afe6

RFQ closes Fri 30 May 2025 11:59pm, Cbr time

- Security: Minimum NV1

- Locations: DSTG Fairbairn, Russell (Cbr), Fishermans Bend (Mlb), Edinburgh (Adl) + WfH as agreed

- Estimated start: Tue 01 Jul 2025 or can join project team thereafter as agreed

- Term: 12 mths + 2 x 12 mths

Background

This project will enable Defence to develop and deploy AI-enabled defence capabilities at scale and of national significance.

About the Project

The project will undertake research and delivery of a ModelOps Platform to enable deployment of AI apps at scale, a critical capability of national significance. It will incorporate modern cloud-based, “X-as-Code” infrastructure technologies and practices. It will host a generic suite of integrated tools and features, customisable for diverse use cases across security classifications. The platform is currently at MVP status making heavy use of open-source tools and technologies. The project team will extend, upgrade and re-align it to Defence enterprise architecture standards, tools and technologies and in full conformance to security requirements.

The project also entails development of set of standards for interchange of AI models, data and test reports between Defence and allies. These standards are at MVP status and require extension to cover additional AI tasks.

Project Work

- Design, Develop, and Test ModelOps platform and MLOps pipelines using AWS and/or Azure Devops CI/CD and Infrastructure as Code, Configuration as Code and containerised workloads (e.g. Docker and Kubernetes).

- The Platform will enable DSTG data specialists/ ML engineers: to store and retrieve analytics data; automate reports using LLMs; apply NLP; and develop machine-readable API’s.

- Collaborate with AI researchers across DSTG, academia and industry to test and validate the Platform for Defence classified environments.

- Set up and configure new clusters (standalone and existing networks).

- Implement test, evaluation, validation and verification (TEVV) practices and pipelines.

- Implement NIST’s test harness for benchmarking.

- Develop model and data metadata standards to allow collaboration between diverse toolchains.

- Develop exemplar DataOps and ModelOps pipelines.

- Support AI technology dev, config and implementation within approved Defence ICT environments.

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Please respond by Wed 28 May 2025 and attach your CV in Word format

Sam Bartone 0416 100 606

RFO-ALERT_202505.25A.