Client-Facing AI Solutions Engineer

Affinda; City of Melbourne; On-site; AUD 89,000 - 95,000; Full time

Job summary

Affinda is seeking a role to build AI solutions for enterprise clients alongside our senior engineers. You will work on retrieval systems, agents, integrations into client stacks, and the evaluation pipelines that prove the system works before going live.

This role involves onsite discovery, sitting inside the client's team during build and deployment, and owning real pieces of the build that grow over the year.

Qualifications

• Proven software development experience beyond coursework.
• Hands-on AI development with LLMs or RAG pipelines.
• Ability to engage with clients on-site during discovery.

Responsibilities

• Build features and services inside client solutions: retrieval pipelines, agents, APIs.
• Write and run evaluations. Golden datasets, precision and recall measures, and results that justify a decision instead of instinct.
• Use AI to write software. Refine prompts, close the loop between generated code and code that runs and passes tests.
• Attend discovery sessions on site. Ask your questions, including the awkward ones.
• Support production deployment and hand the solution across cleanly. The client's team must be able to run it once we step back.
• Watch cost and security in what you build. Inference costs climb quietly at scale, and a security or compliance concern gets raised the moment you see it.
• Ship in the client's stack. We lean Python, with React when a front end is needed, and you will pick up whatever the client already runs on.

Skills

Experience in software development

Backend skills

AI hands-on

AI-native development

Client-facing collaboration

Tools

Python

APIs

React

Databases

Job description

Affinda is seeking a role to build AI solutions for enterprise clients alongside our senior engineers. You will work on retrieval systems, agents, integrations into client stacks, and the evaluation pipelines that prove the system works before going live.

This role involves onsite discovery, sitting inside the client's team during build and deployment, and owning real pieces of the build that grow over the year.