Software Engineer - Enterprise AI Enablement
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- Python, R, Spark, SQL, AWS Sagemaker, statistical & ML expertise
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- Implement AI initiatives to improve pricing processes and decision support
- Experience delivering AI, ML, analytics or automation solutions
- AI engineering, cloud technologies, agentic AI, generative AI, MLOps
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- Technical authority on integrating Generative AI into enterprise environments
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Lead AI Engineer
- Build and deploy Agentic AI solutions to accelerate Product Development
- 8+ years software engineering, proven LLM and Agentic AI experience
- LangChain, LangGraph, AutoGen, Python, Java, Kubernetes, multi-cloud
- Work on cutting‑edge agentic AI and enterprise GenAI initiatives
- Strong culture, modern tech stack, and opportunity for career growth
- Contract engagement offering a hybrid working environment
• Hybrid working environment with strong flexibility
• Work on cutting‑edge agentic AI and enterprise GenAI initiatives
• Strong culture, modern tech stack, and opportunity for career growth
The CompanyOur client is a large, forward‑thinking banking organisation with a national footprint and a strong global presence. They are recognised for continuous innovation, stability, and a commitment to building intelligent, AI‑driven solutions that transform the way their teams and customers engage with technology. With a modern structure and collaborative environment, they empower employees to influence major enterprise programs and shape the organisation’s AI future.
The RoleIn this role, you will support our client’s Enterprise AI Enablement team as they build the foundation for scalable, AI‑native systems across the organisation. You will help deliver backend systems, data pipelines, and automated workflows that power next‑generation AI agents. You will work alongside data scientists, platform teams, and AI specialists to implement LLMOps best practices and enable enterprise‑wide adoption of Generative AI.
Key Responsibilities
- Design and develop scalable backend systems for AI‑native applications
- Build automated workflows for enterprise AI agents
- Implement LLMOps practices for model deployment and monitoring
- Integrate AI capabilities into business workflows
- Contribute to reusable libraries, governance frameworks, and engineering best practices
- Enhance enterprise RAG systems and knowledge infrastructure
- Proficiency in Python and backend software engineering
- Hands‑on experience with CI/CD, Docker, Kubernetes, and cloud deployments
- Understanding of LLMOps, model lifecycle, and operational AI workflows
- Experience with frameworks such as RAG, LangChain, LangGraph, LlamaIndex, MCP, or Google ADK
- Background in building or supporting scalable, production‑grade systems
- Ability to work in an agile DevOps environment
- Bonus: exposure to graph databases or knowledge graphs
- Hybrid working, supportive leadership, and a culture that values innovation
- Opportunity to contribute to high‑impact, enterprise‑wide AI transformation
- Access to modern tooling, strong professional development pathways, and large‑scale engineering challenges
For more information, click APPLY to register your interest, or alternatively, you can call Tex in our Sydney office on +61 2 9087 6214.
About TEKsystemsWe’re partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a committed team working with over 6,000 clients across North America, Europe and Asia‑Pacific. As an industry leader in talent solutions and technology services, we work with progressive leaders to drive change. That’s the power of true partnership. TEKsystems is an Allegis Group company.