About Doghouse
Doghouse Agency develops software products and digital platforms for government and enterprise organisations across Australia. Our engineering team builds production software incorporating LLM's, RAG, semantic search, vector databases and workflow automation to solve real business problems.
About the Role
We are seeking a Software Engineer (Artificial Intelligence) to design, develop, implement and support production software applications across our SaaS products, client platforms and internal engineering systems.
This is a hands on software engineering role focused on delivering secure, scalable and production ready software solutions using modern software engineering practices and cloud native technologies.
Key Responsibilities
The successful applicant will:
- Research, analyse and evaluate business and technical requirements for software applications incorporating LLM's, RAG, semantic search and workflow automation.
- Design and develop software architecture for production applications, including RAG pipelines, conversational interfaces, semantic search services, embedding-based retrieval systems and agent-based workflows.
- Develop, maintain and optimise software using Python, PHP (Laravel), JavaScript/TypeScript and SQL in accordance with system requirements, technical specifications and software engineering standards.
- Integrate commercial and open-source LLM's, vector databases, APIs and orchestration frameworks into new and existing software applications.
- Design, develop and maintain data ingestion, extraction, transformation, embedding and indexing pipelines supporting semantic retrieval systems and conversational applications.
- Train, evaluate and optimise machine learning models, embedding strategies, retrieval performance and application behaviour using operational metrics and evaluation frameworks.
- Test, debug, diagnose and resolve software defects while ensuring software complies with engineering, testing, security and quality assurance standards.
- Deploy, manage and support software applications across cloud environments using AWS and automated deployment pipelines.
- Identify technology limitations, software deficiencies and automation opportunities, recommending improvements to software architecture, engineering processes and business operations.
- Monitor production systems, collect and analyse operational metrics, and implement continuous improvement strategies to improve reliability, scalability, performance and operational efficiency.
- Analyse structured and unstructured datasets to improve retrieval accuracy, embedding quality, application behaviour and overall software performance.
- Prepare, update and maintain technical documentation, software documentation and operational procedures.
- Provide technical advice and contribute to software architecture, technology evaluation, framework selection and implementation planning.
- Identify and mitigate software performance, security, privacy and operational risks throughout the software development lifecycle.
Essential Skills & Experience
Applicants should demonstrate commercial experience across the majority of the following technologies and disciplines.
Software Engineering
- Developing production software using Python, and one or more of PHP (Laravel), JavaScript/TypeScript and SQL.
- Designing REST APIs and scalable software architectures.
- Writing, testing, debugging and maintaining production software using modern software engineering practices and Git-based workflows.
LLM's & Machine Learning
- Commercial integration of LLM's, including OpenAI, Anthropic, Mistral or open-source models.
- RAG, semantic search, embeddings, prompt engineering, structured outputs and conversational applications.
- Machine learning concepts including model evaluation, inference optimisation and retrieval optimisation.
Data Engineering & Retrieval Systems
- Vector databases including PostgreSQL/pgvector, Pinecone, Weaviate, ChromaDB or equivalent technologies.
- Designing and maintaining data extraction, transformation, indexing and embedding pipelines supporting production software.
Frameworks & Cloud Platforms
- AI orchestration frameworks such as LangChain, n8n or equivalent technologies.
- AWS or Azure cloud platforms.
- Docker, Linux, CI/CD pipelines and Git.
Professional Skills
- Strong analytical and problem-solving skills, with the ability to translate business requirements into production software.
- Excellent written and verbal communication skills.
- Ability to work independently and collaboratively within Agile software engineering teams.
- Demonstrated commitment to continuous learning and emerging software engineering technologies.
Qualifications
- A degree in Computer Science, Software Engineering, Information Technology or a related discipline, or equivalent demonstrated commercial experience.
- Minimum 1–3 years' commercial software engineering experience designing, developing and deploying production software applications.
- Demonstrated experience developing software incorporating LLM's, RAG, vector databases and semantic retrieval technologies.
- Experience developing cloud-native applications using modern software engineering practices.
Highly Desirable
Experience with one or more of the following will be highly regarded:
- Kubernetes and container orchestration.
- Distributed systems and large-scale architecture.
- TensorFlow or PyTorch.
- LlamaIndex or similar orchestration frameworks.
- Fine tuning or parameter-efficient tuning of language models.
- Open-source model deployment (e.g. Llama, Qwen, Mistral, Falcon or similar).
- Model Context Protocol (MCP) and agent-based software systems.
- Knowledge graph or GraphRAG implementations.
- GPU deployment and inference optimisation.
- AI evaluation and observability frameworks.
- Secure software engineering and enterprise security practices.
- Enterprise SaaS products, government digital platforms or large-scale web applications.
What We Offer
- Opportunity to work on production software deployed across government and enterprise environments.
- Exposure to modern software engineering, cloud platforms and emerging language model technologies.
- A collaborative engineering environment focused on technical excellence, automation and continuous improvement.
- Ongoing professional development and opportunities to work with emerging technologies.
How to Apply
Applications should include:
- A current CV.
- A cover letter addressing the essential skills and experience.
- Links to GitHub repositories, technical publications or examples of production software developed (where available).
Pay: $85,000.00 – $95,000.00 per year
Work Authorisation:
Work Location: In person
