A leading conversational AI company provides a platform that helps brands deliver concierge-level customer experiences. Its technology enables well-known enterprises to deploy AI agents that power personalised, deeply satisfying interactions across voice, chat, email, SMS and other channels. The company is redefining customer experience, moving from support tickets and hold music to faster resolutions, richer conversations and stronger relationships.

Backed by world-class investors, it is an in-office business driven by a shared commitment to excellence and velocity.

The company is seeking an Customer Engineer to own the end-to-end delivery of AI agent builds for strategic customers. This is a highly technical, customer-facing role within a newly created Agent Builder team, which brings greater specialisation and focus to build quality. You will work hands-on to deliver enterprise-grade agents, writing and configuring key components, validating integrations and ensuring agents perform reliably at scale, while engaging with senior technical stakeholders on the customer side.

You will partner with customers and internal teams to define success, turn requirements into build plans and deliver agents that make a real impact on the customer’s business. Working closely with Agent PMs, Agent Success, Engineering and GTM teams, you will create tight feedback loops, surface gaps and influence the evolution of the company’s agent-building platform based on real customer needs. The role is ideal for someone who thrives in quick-moving environments, enjoys shipping customer-facing technical work and can balance hands-on execution with structured thinking.

Key Responsibilities:





- Own the end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation and production deployment.
- Design and engineer the core agentic logic that governs agent behaviour, applying engineering principles to optimise quality, reliability and correctness across non-deterministic model outputs.
- Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant and predictable agent performance in real-world scenarios.
- Architect, build and test integrations with customer systems (e.g. data pipelines, CRMs, ticketing systems), including the tools, APIs and workflows needed for reliable deployments at scale.
- Work with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines.
- Diagnose, debug and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs and model behaviour.
- Design evaluation and regression-testing frameworks to validate agent behaviour against ground truth and guard against performance drift.
- Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements.
- Partner closely with APMs, Engineering, Design and Go-To-Market teams to deliver consistent,



repeatable, best-in-class agent builds.

Key Qualifications:

- Ideally 3+ years of relevant experience in a technical customer-facing role (e.g. solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product management or similar).
- Strong technical foundation, with comfort writing code, working with APIs and building and validating integrations end-to-end.
- Experience delivering production-grade customer solutions that require structured execution, testing, validation and iteration.
- Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans and drive delivery.
- Comfort working in quick-moving, ambiguous environments where you shape solutions as much as you implement them.

Experience in the following areas would be a plus:

- Experience building with or around LLMs and AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.).
- Experience with enterprise SaaS integrations (e.g. ticketing systems, CRM, data pipelines) and the associated security and compliance considerations.
- A Computer Science, Engineering or Math degree, or equivalent technical experience.
- Strong product instinct, including the ability to write crisp PRDs, define success metrics and feed customer insight back into the product roadmap.

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📌 Customer Engineer (Sydney)
🏢 Tech Recruit
📍 Sydney