We’re partnering with a major enterprise organisation that is building out an Enterprise AI Enablement capability and looking for strong software engineers to design, build and operate production-grade AI systems.

This is not a data science or research role. It is a hands-on software engineering position for engineers who understand how to take AI-enabled products from concept into reliable, scalable production systems.

You’ll work across a range of AI use cases including customer-facing solutions, internal employee AI, human-in-the-loop agents, headless services, RAG platforms and enterprise knowledge integrations.

What you’ll be doing

- Designing and building production backend services and agentic AI workflows
- Developing RAG-based systems and enterprise knowledge integrations
- Building agents that interact with internal systems and APIs
- Working with MCP, LangChain, LangGraph, Google ADK or similar orchestration frameworks
- Designing prompt and agent evaluation approaches
- Measuring accuracy, reliability, latency and production performance
- Managing model upgrades and understanding their impact on agent behaviour
- Building and maintaining CI/CD and containerised deployment workflows
- Owning solutions across design, development, testing, deployment and production support
- Working closely with data scientists, product teams and platform engineers

What we’re looking for You will be a strong software engineer first, with several years of experience building and supporting production systems.

You should be comfortable discussing:

- System design and architecture
- Distributed systems
- APIs and microservices




- Reliability and failure scenarios
- Maintainability and debugging
- Architectural trade-offs
- CI/CD and containerisation
- Cloud deployment
- Production ownership

Python is the primary language, but strong engineers from Java, C#, Go or TypeScript backgrounds can also be considered if you have moved into Python or can transition comfortably. You should also have genuine hands-on experience with modern AI engineering concepts such as:
- RAG
- MCP
- Agent orchestration
- LangChain / LangGraph / ADK
- Prompt engineering
- Agent evaluation
- LLM observability
- Production AI workflows

GCP is the primary environment, although strong AWS/Bedrock or Azure experience is highly transferable.

Important

We are not looking for candidates whose experience is primarily prompt engineering, AI experimentation or model research. This role requires solid production software engineering fundamentals.

You should be able to clearly explain systems you have personally designed, built, deployed and supported in production.

Why consider it

You’ll join a team working on enterprise-scale AI capability with real production use cases already in flight. The work spans agentic systems, internal AI platforms, knowledge layers and reusable services, with a strong focus on engineering quality rather than experimentation.

There are opportunities across multiple seniority levels for engineers who can demonstrate strong technical depth, design capability and production ownership.

Salary based on experience - $140,000 - $240,000 total package plus annual bonus.

Apply now or send your CV directly to [email protected]

📌 Senior Software Engineer - AI Enablement (Sydney)
🏢 Lanson Partners
📍 Sydney