Senior AI Engineer Full Time

About Evora

Evora is a Melbourne-based healthcare data and analytics consultancy. We deliver analytics, reporting, data migration, and platform engineering for Australian health services. We are building a new product as an extension of our existing consultancy work and are looking for an engineer to lead the build.

The role

You will be the primary engineer on a new product build, working directly with Evora’s leadership. The product is an AI-powered data service running on Microsoft Azure. The work involves building a stateless backend service that integrates with Azure OpenAI, a managed data layer using cloud-native storage and query tooling, and integrating with Microsoft conversational platforms.

This is an applied AI engineering role focused on building production systems that integrate large language models, not a research or model training role.

This is a hands-on build role, not an architecture or advisory role. You will write the code, deploy the infrastructure, run the AI-assisted development workflow, and own delivery.

This is an initial 6 month contract with option for extension.

Required skills

• Strong Python (or equivalent backend language) with experience building production HTTPS services
• Demonstrated experience using AI-assisted development practices in real projects: coding agents (Claude Code, Cursor, Aider, or equivalent), Git worktrees for parallel work, persistent skills or rules files, and review patterns that scale to AI-generated code volume
• Experience integrating with LLM APIs (Azure OpenAI, OpenAI, Anthropic, or equivalent), including prompt engineering, retrieval-augmented generation, and structured output handling
• Working knowledge of SQL and at least one analytical query engine (DuckDB strongly preferred; Synapse, Databricks, or similar acceptable)
• Comfortable working with Azure: Container Apps, Azure OpenAI, ADLS Gen2, Blob Storage, Key Vault, Entra ID, API Management, Log Analytics
• Experience designing stateless services with proper structured logging, externalised configuration, audit logging, and error handling
• Able to write clear technical documentation and work independently with minimal supervision
• Able to present technical concepts to a non-engineering audience for knowledge sharing sessions

Highly regarded

• Experience setting up and networking Azure environments using Terraform or Bicep
• Experience with multi-tenant Entra ID applications and cross-tenant Azure resource access patterns
• Experience with Microsoft Copilot Studio or Azure AI Foundry Agent Service, including Teams channel deployment and adaptive cards
• Experience with vector search and embedding-based retrieval (Azure AI Search, pgvector, or in-process vector libraries)
• Experience with SQL parsing and validation tooling (sqlglot or equivalent)
• Familiarity with healthcare data, clinical systems, or other regulated industries

What we offer

A focused, well-scoped product build with direct access to Evora’s leadership. The work is technically interesting and commercially important. The candidate will have meaningful ownership of the engineering decisions within an agreed architecture, and will be expected to share their AI-assisted development practices with Evora’s broader consulting team through periodic showcases.

Selection process

We run a deliberate five-stage process designed to assess both technical depth and communication. The full process runs across approximately six weeks.

1. CV triage (week 1 to 2). Desktop review of skills against the required and highly regarded lists above.
2. Informal chat (week 3 to 4). A short conversation with Evora leadership to assess communication, working style, and cultural fit.
3. Take-home mini-project (week 5). A scoped technical exercise designed to be completed in approximately one week alongside other work. The brief covers a small AI-powered data service integrating an LLM with structured data on Azure, with infrastructure-as-code, retrieval, and a demonstrable result. We will pay candidates AUD$500 on submission of the take-home in recognition of the time required. AI-assisted development is encouraged and candidates will be asked to describe how they used it.
4. Showcase (week 6). A one to one-and-a-half hour session with Evora leadership covering a walkthrough of the take-home submission, decisions made, tradeoffs, and questions. This is both a technical review and a test of executive communication.
5. Decision (week 7). Reference checks, internal decision, and offer.

The take-home and showcase together carry more weight than the CV in the final decision.