Senior Agentic Software Engineer

Opus Recruitment Solutions; City of Melbourne; On-site; AUD 120,000 - 180,000; Full time

Job summary

Opus Recruitment Solutions seeks an AI-focused software engineer to design and ship LLM-powered applications for enterprise clients. You will build backend services, data pipelines, and integration layers to keep AI systems reliable in production.

You will translate business problems into scalable AI solutions, collaborating with stakeholders to drive AI adoption in fast-moving environments and shaping end-to-end solution design from discovery to deployment.

Qualifications

• Hands-on engineering across backend, ML engineering, data science, or applied AI.
• Experience building and shipping production systems used by real users.
• Hands-on experience with LLMs, RAG, agents, or GenAI applications.

Responsibilities

• Design and build LLM-powered applications including RAG systems and AI automation tools.
• Build backend services, APIs, data pipelines and integration layers for production AI.
• Translate complex business problems into scalable AI solutions with measurable impact.
• Collaborate with technical and non-technical stakeholders to guide AI adoption.

Skills

Python

LLMs

RAG architectures

Agentic workflows

Production systems

Tools

AWS

GCP

Azure

APIs

Job description

Partnered with 1 of the worlds leading AI firms - who have gone from 30 to 150 inside of 2 years - spearheaded by their cutting edge AI solutions and AI partnerships.

The company works with ambitious enterprise clients to design, build, and deploy AI applications that solve complex operational and commercial problems. This includes LLM-powered workflows, agentic systems, RAG applications, automation tools, and AI products that are embedded into how businesses actually operate.

The Role

• Designing and building LLM-powered applications, including RAG systems, agentic workflows, and AI automation tools using Python and modern AI engineering tooling.
• Building backend services, APIs, data pipelines, and integration layers that allow AI systems to operate reliably in production.
• Translating complex business problems into scalable AI solutions that create measurable impact.
• Working directly with technical and non-technical client stakeholders to understand requirements, challenge assumptions, and guide AI adoption.
• Own technical solution design from discovery through to deployment and iteration.

Your Profile

• Strong hands-on engineering experience across backend software engineering, ML engineering, data science, or applied AI.
• Experience building and shipping production systems used by real users.
• Hands-on experience with LLMs, RAG architectures, agents, tool-calling, or GenAI applications.
• Experience working with cloud environments such as AWS, GCP, Azure, or similar.
• Comfort operating in ambiguous, fast-moving environments where you need to figure things out quickly.
• A genuine interest in applied AI and how it can change how organisations work.