Senior Software Engineer AI Development
Location : Australia (remote-first AU-based)
Employment type : Full-time
Salary : Competitive senior market rate
The problem space
Refactor are partnering with an Australian AI startup with a production AI platform enterprise customers and a growing SaaS offering.
Were now extending the platform to support an LLM-agnostic agentic AI assistant that integrates across enterprise systems and helps everyday business users plan work prioritise tasks and structure their work experience.
This role exists because the system is no longer experimental. Retrieval quality orchestration latency security and UX are all priorities in our ongoing product development.
What were building
The platform is built around production-grade RAG and agentic workflows.
Backend :
A Java-based API platform that :
- Orchestrates LLM calls
- Executes multi-step agent workflows
- Integrates with enterprise systems
- Enforces tenancy security and access controls
Retrieval layer
Weaviate as the primary vector databaseHybrid search (vector keyword)Tuned chunking embeddings and rerankingFrontend :
React application used daily by non-technical business usersSurfaces agent outputs plans tasks and recommendationsAI layer
LLM-agnostic (supporting models from Anthropic Mistral & Open AI)Support for cloud private and sovereign deploymentsExplicit cost latency and reliability controlsThe assistant is agentic by design. The planning sequencing actions querying multiple systems and producing structured outputs users can act on.
What youll be responsible for :
Youll be a hands-on senior engineer contributing across backend and frontend with a primary focus on core product development.
Backend & product engineering :
Strong T-shaped engineering skills with deep expertise in backend Java development and practical knowledge across related technologies required to deliver production-ready systemsExperience with AWS and cloud technologies CI / CD pipelines system configuration unit and manual testing and integrations with external systems such as web crawlers and enterprise API servicesDeveloping LLM orchestration and agent execution layersImplementing and maintaining enterprise integrations (documents tasks calendars knowledge systems)Ensuring APIs are versioned stable and suitable for enterprise time horizonsRAG & retrieval systems :
Designing and evolving production RAG pipelinesOwning :
Document ingestion and preprocessingChunking strategies and embedding lifecycle managementRetrieval tuning hybrid search and rerankingExperience in database-level optimisations query and retrieval performance tuning and embedding lifecycle management to improve accuracy consistency and efficiency in production datasetsImproving grounding relevance and consistency across real customer datasetsHandling retrieval failure modes and partial or stale data scenariosSystem quality scale & reliability
Optimising latency throughput and cost across retrieval and model callsImplementing observability (structured logging metrics tracing)Building guardrails timeouts and fallback behaviour for agent workflowsExpertise in observability structured logging metrics tracing and automated testing strategies to ensure robust scalable and reliable production systemsContributing to tenant isolation data boundaries and security controlsFrontend contribution (important but secondary) :
Practical understanding of frontend requirements enabling close collaboration with UI teams to align API design and deliver fully integrated production-ready featuresTranslating backend capabilities into clear usable interfaces for non-technical usersContributing directly to the React codebase where appropriateEnsuring tight alignment between API design and frontend needsReact experience is not required but practical exposure is a strong advantage.
Product-driven engineering
Translating real user workflows into concrete product featuresMaking pragmatic trade-offs between accuracy explainability performance and UXIterating based on production feedback not assumptionsWhat were looking for
Were looking for engineers who have already built and managed sovereign AI deployments in production environments.
Required :
5 years professional software engineering experience2 years building RAG-based systems used in productionStrong backend experienceHands-on experience with :Vector databasesEmbeddings chunking and retrieval strategiesLLM orchestration (framework-based or custom)Experience supporting production customer-facing systemsValued :
Experience with retrieval quality and failure modesExperience with agentic workflows beyond simple chainsSaaS or multi-tenant architecturesReact experience or strong API-first frontend collaborationEnterprise or regulated environmentsAWS private cloud or hybrid deploymentsWhy this role might be interesting
Youll work on real RAG and agentic systems designed for scale. Youll be working at the cutting edge as open source models mature helping evaluate and deploy the best-fit models responsibly in private enterprise environmentsYoull be involved with evolving the backend architecture and user-facing productCustomers are already live so your work has immediate impactSmall senior geo-distributed team with high autonomy and professionalismAustralian company building globally relevant enterprise AIWhen you apply were interested in :
What RAG systems youve built or operatedWhere they struggled or failedHow you approached trade-offs in retrieval latency and UXWhat kind of AI product you want to help build nextThis role is a fantastic opportunity to join a growing start up who have already landed some major accounts and now ready to expand. Youll join an exisiting team who is increibly talented.
What are you waiting for - get applying now!
James Farrey
Founder & Director
#SCR-james-farrey
Required Experience :
Senior IC
Key Skills
Spring,.NET,C / C++,Go,React,OOP,C#,AWS,Data Structures,Software Development,Java,Distributed Systems
Employment Type : Full Time
Experience : years
Vacancy : 1