Role details
Own the AI architecture behind a live agentic platform handling real customer conversations across voice, web and SMS, reporting directly to the CEO.
You'll lead the technical direction of a conversational and agentic AI platform, owning everything from LLM orchestration and RAG pipelines through to cloud infrastructure, production reliability and the engineering team itself. This is a hands-on leadership role. You'll be writing code, diagnosing production incidents and shaping AI architecture alongside managing a growing team.
The role is hybrid or remote, based out of Sydney. You'll work closely with the co-founders on engineering priorities, translating product and commercial goals into clear technical plans. The stack spans Azure and AWS, with containers, Infrastructure as Code, CI/CD, distributed tracing and modern AI tooling throughout.
Early-stage means you'll carry real ownership across a wide surface area. There's no large platform team to hand things off to, so you'll need to be comfortable moving between agent architecture, cloud operations and people leadership in the same week. What you get in return is genuine influence over how the platform is built, the ability to make architectural decisions that stick, and a front-row seat as the product scales.
What You'll Do
- Own agentic AI architecture across LLM orchestration, RAG, tool calling, memory, model routing and human-in-the-loop workflows.
- Build and own the AI quality framework covering automated evaluation, regression testing, release gates and production observability.
- Own cloud infrastructure across Azure and AWS, including CI/CD, IAM, multi-tenant security, incident response and FinOps.
- Lead and grow the engineering team, setting standards, managing delivery and staying hands-on across complex technical problems.
What You'll Need
- 10+ years of software engineering experience, including senior architecture or technical leadership responsibilities, with strong recent hands-on coding.
- Production experience building agentic or LLM-based systems using orchestration, tool calling, RAG, guardrails and permissioned actions.
- Cloud-native engineering experience across Azure and/or AWS, including Infrastructure as Code, containers, networking and IAM.
- Experience owning multi-tenant, customer-facing production systems and leading teams through incident response and post-incident reviews.
About the Company
They're an early-stage AI technology company building a production agentic platform that automates complex customer interactions across voice, web and SMS. Their agents integrate directly with customer systems to manage multi-step conversations and take real-world actions. The team is growing and investing heavily in conversational intelligence and production engineering capability.
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