Lead the design and delivery of enterprise AI, data platforms, and agentic solutions across cloud-native environments.
28th August, 2026
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