Company Description
Showtime Consulting is a leading provider of Shielded Cloud and Digital Solutions across Australia and New Zealand. We specialise in delivering secure, enterprise-scale technology outcomes within highly regulated environments, supporting government, enterprise, and national security programs.
We partner with organisations undergoing digital transformation, helping them build scalable, modern software solutions that deliver exceptional user experiences and business outcomes.
The Role
We are seeking a highly experienced Senior Data & AI Engineer to join a growing team delivering enterprise-scale Data and AI solutions.
This is a hands-on engineering role that sits at the intersection of Data Engineering, Software Engineering, Machine Learning Engineering, and AI Engineering. You will be responsible for building the data foundations, platforms, pipelines, and enterprise integrations required to support AI, Generative AI, and Agentic AI solutions in production environments.
The successful candidate will have proven experience delivering end-to-end AI and data solutions from concept and architecture through to deployment, adoption, and measurable business outcomes. You will collaborate closely with data scientists, software engineers, architects, and business stakeholders while helping uplift engineering capability across the organisation.
Key Responsibilities
Design, build, and maintain scalable data platforms, pipelines, and AI engineering solutions
Deliver end-to-end AI initiatives from concept and architecture through to production deployment and operational support
Develop robust data ingestion, transformation, orchestration, and integration capabilities across enterprise systems
Design and implement cloud-native AI platforms and production-ready machine learning solutions
Build and optimise APIs, microservices, and event-driven architectures supporting modern AI applications
Develop and deploy AI agents and agentic workflows integrated with enterprise platforms and business processes
Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and modern LLM frameworks
Collaborate closely with data scientists to operationalise models and accelerate the delivery of AI solutions
Establish best practices across CI/CD, infrastructure as code, security, governance, monitoring, and Responsible AI
Provide technical leadership, mentoring, and coaching to engineers as they transition into AI engineering capabilities
Troubleshoot complex platform, data, and AI-related issues in production environments
Evaluate emerging AI technologies and contribute to strategic technology direction and innovation initiatives
What You'll Need
Strong hands-on experience across Data Engineering, Software Engineering, Machine Learning Engineering, and AI Engineering
Proven experience delivering enterprise-scale data or AI solutions from concept through to production
Advanced proficiency in Python and SQL
Strong experience building APIs, microservices, and distributed systems
Experience working with event-driven architectures and modern integration patterns
Expertise designing and delivering cloud-based data and AI platforms
Hands-on experience with Spark, Databricks, or equivalent big data technologies
Strong understanding of Large Language Models (LLMs) and modern Generative AI concepts
Practical experience with embeddings, vector databases, Retrieval-Augmented Generation (RAG), and agent orchestration frameworks
Experience implementing CI/CD pipelines, Infrastructure as Code, monitoring, observability, and platform automation
Strong knowledge of security, governance, compliance, and Responsible AI practices
Excellent communication, stakeholder engagement, and problem-solving capabilities
Proven experience mentoring engineers and leading technical delivery teams
Desirable Experience
Experience delivering Agentic AI and autonomous workflow solutions within enterprise environments
Exposure to MLOps, ModelOps, and AI platform engineering practices
Experience with modern AI frameworks such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar
Knowledge of containerisation and orchestration technologies including Docker and Kubernetes
Experience working across Azure, AWS, or Google Cloud AI and data services
Exposure to streaming and real-time data platforms such as Kafka, Event Hubs, or equivalent
Experience operating within large-scale enterprise, consulting, government, or regulated environments
Knowledge of data governance, privacy, and AI compliance frameworks
Qualifications
Bachelor's degree in computer science, Software Engineering, Data Science, Information Technology, or a related discipline
8-15+ years of experience across software, data, platform, or AI engineering roles
Demonstrated experience delivering production-grade AI and data solutions at enterprise scale
Strong architectural, analytical, and troubleshooting capabilities
A collaborative leadership style with a passion for mentoring and building engineering capability
Commitment to delivering secure, scalable, and high-quality technology solutions
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