The Agentic AI Engineer will design, build and deploy production-grade AI solutions that improve productivity, decision-making and operational performance across the company’s Industries. You will also focus on large language models, agentic workflows, retrieval-augmented generation, business-system integrations and intelligent automation.

Company Profile:

Our client is a wholly owned Australian company manufacturing a large range of steel products including Garden Sheds and Outdoor Buildings. From its manufacturing facility in Brisbane, our client distributes an extensive range of outdoor storage products throughout Australia, as well as exporting to the Pacific region and Europe. They have been a major supplier of outdoor storage products for over 55 years. The good reputation they have built is now being recognized throughout Australia and rapidly expanding to overseas markets including New Zealand and Europe.

This is an exciting opportunity to join a growing organisation that is investing in AI, e-commerce, and digital transformation. As an Agentic AI Engineer, you will work closely with technology and business teams to design, build, and deploy production-ready AI solutions, including LLM applications, RAG systems, and intelligent agent workflows. The role offers the opportunity to work on practical AI use cases that improve productivity, automate processes, connect business systems, and deliver measurable operational outcomes.

Duties and Responsibilities:

• Design, build and deploy LLM-powered applications and agentic AI workflows.

• Develop AI agents capable of using approved tools and APIs, completing multi-step tasks and escalating decisions for human approval where required.

• Build RAG solutions across structured and unstructured business information.

• Develop document-ingestion, chunking, embedding, metadata, retrieval, reranking and response-grounding pipelines.

• Integrate AI solutions with ERP, inventory, manufacturing, sales, finance, supply-chain and customer-service systems.

• Build secure and maintainable APIs connecting AI applications with business systems and databases.

• Move solutions from proof of concept through testing, deployment, monitoring and ongoing production support.

• Establish automated testing and evaluation for accuracy, retrieval quality, hallucination, latency, reliability and cost.

• Implement appropriate authentication, access controls, audit trails, guardrails and data-security protections.

• Monitor and optimise model usage, response times, infrastructure costs and overall system performance.

• Maintain clean, tested and well-documented Python code.

• Work with business stakeholders to convert operational problems into practical AI solutions.

• Collaborate closely with Absco’s Australian and Philippine teams.

• Document architecture, APIs, deployment processes and support procedures.

• Monitor emerging AI technologies and recommend commercially valuable applications for the business.

Requirements

Must-have Skills / Qualification:

• At least 2 years’ commercial experience building and deploying AI solutions.

• Demonstrated experience taking LLM, RAG or agentic AI solutions from experimentation through to production.

• Strong Python / C# .Net development skills.

• Practical experience with:

- Large language models and LLM APIs

- Agentic AI and multi-step workflows

- Tool and function calling

- Retrieval-augmented generation

- Vector databases and semantic search

- LangChain, LangGraph or comparable frameworks

- REST APIs, webhooks and system integrations

- Azure, AWS or Google Cloud Platform

• Strong SQL skills and experience working with structured and unstructured data.

• Experience building production APIs using FastAPI or similar frameworks.

• Knowledge of prompt design, structured outputs, response grounding and hallucination reduction.

• Experience with Git, automated testing, Docker, CI/CD and production monitoring.

• Understanding of AI security risks, including prompt injection, inappropriate data access and sensitive-information handling.

• Ability to communicate technical concepts clearly to non-technical stakeholders.

• Strong written and spoken English.

• Ability to work independently while collaborating effectively with a distributed team.

• Strong ownership and accountability from concept through to deployment.

• A practical and commercially focused approach to technology.

• Curiosity and a willingness to test and learn quickly.

• High standards for quality, security and reliability.

• Comfort working through ambiguity and solving complex problems.

• A strong focus on delivering useful business outcomes, not demonstrations alone.

• Clear communication and a collaborative working style.

• Discipline in documenting systems and transferring knowledge.

• The ability to balance delivery speed with appropriate engineering controls.

Advantageous but not required:

• Development experience using ASP.NET, C#, .NET Core and Python, including integrating AI solutions with existing .NET applications and business systems.

• Azure OpenAI, Azure AI Foundry or the broader Microsoft technology environment.

• Microsoft SQL Server, Microsoft 365, SharePoint, Microsoft Graph or Power Platform.

• Experience with pgvector, Pinecone, Qdrant, Weaviate or Azure AI Search.

• Knowledge of ERP, manufacturing, inventory, supply-chain, finance or customer-service systems.

• AI observability and evaluation tools such as LangSmith, Phoenix or MLflow.

• Human-in-the-loop approval workflows and auditable agent actions.

• Event-driven architecture, queues, background workers and workflow orchestration.

• OCR, document intelligence, speech transcription or computer-vision applications.

• Front-end development using React, TypeScript or similar technologies.

• Experience quantifying the commercial benefits of technology projects.