Introduction

We believe human progress will come from augmenting AI to the way we work. We help organisations scale results, not their headcount, with AI and automation. We achieve this through two core business areas: AI Readiness and AI Agents. If you want to get in on the ground floor of a fast-paced startup where your efforts have a direct impact on the success of our mission, we’d love to hear from you.

Role summary

We are seeking a Senior Engineer to design and build robust, scalable, and cost‑efficient data platforms that enable AI and analytics at enterprise scale. You’ll own everything from raw data ingestion and transformation to serving feature stores that power production‑grade generative‑AI and machine‑learning workflows.

This role aligns with our employee archetypes The Engineer. The Engineer designs robust, scalable, cost-aware solutions, hardens them with guardrails, and measures impact end-to-end.

Responsibilities and duties

Insight Translation

- AI leadership: Develop and execute AI strategies to achieve business objectives and expand AI capabilities.
- Client recommendations: Collaborate with business and technical stakeholders to understand objectives and translate them into data‑engineering requirements.
- Communication: Communicate architecture decisions, trade‑offs, and roadmap progress in clear, compelling language.
- Research and innovation: Stay updated on industry trends, competitive landscape, and emerging technologies to inform AI strategies.

Change Enablement

- Project management: Leads end-to-end project management for data engineering initiatives, including scoping, planning, stakeholder communication, and delivery of outcomes aligned to business objectives.
- Stakeholder management: Manage multiple commercial and technical stakeholders effectively. Able to effectively manage executive stakeholders.
- Team leadership: Mentor junior engineers, championing best practices in code reviews, CI/CD, and documentation.
- Work with ambiguity: Adapt to changing toolkits, models, and scopes, and manage volatile POCs and prototypes.
- Collaboration:



Work closely with the sales, marketing, product, and delivery teams to align AI efforts with overall business objectives.
- Recruitment: Supporting the expansion of the team as we grow.

AI Orchestration

- Solution Architecture: Design end-to-end systems that combine models, workflows, automation, and APIs.
- Technical Leadership: Build data ingestion, transformation, and feature‑store pipelines that power LLMs and ML models in production.
- Monitoring: Embed automated data‑quality tests, monitoring, and cost‑controls to keep workloads safe and efficient.
- Use Case Delivery: Lead the development and deployment of AI initiatives that address real-world business needs.
- Automation Integration: Combine AI models with workflow automation and decision systems to streamline processes.

Technical Versatility

- Tool Fluency: Design and implement batch and streaming ELT/ETL workflows using Python, SQL, dbt, Airflow, Spark, Snowflake, Databricks, or similar technologies.
- Stack Agility: Adapt quickly across cloud, open-source, and low-code/no-code toolchains to meet solution needs.
- Integration Skills: Integrate diverse data sources (APIs, events, files, warehouses) and optimise storage and compute across cloud environments.
- Evolving landscape: Continuously research, evaluate new technologies and integrate promising tools into the delivery toolkit.

Engineering Mindset

- Data engineering: Designs, builds, and maintains scalable data pipelines, robust data models, and production-grade machine learning solutions.
- AI Ops & Scalability: Introducing repeatable and scalable AI processes.

Ideal candidate Skills & Experience

- Engineering Experience:



5+ years of experience in building scalable ETL/ELT pipelines, developing robust data models, and working with modern data stacks (e.g. dbt, Airflow, Snowflake, Databricks, cloud platforms).
- AI Experience: Experience in data science, including hands-on experience with Generative AI.
- Systems design: Demonstrated ability to design and implement AI application workflows by orchestrating multiple tools, APIs, and models to deliver end-to-end, production-ready solutions.

Mindset & Capabilities

- Business storytelling and influence: Experienced at explaining findings and complex ideas to both technical and non-technical stakeholders.
- Resilience, flexibility and agility: Demonstrated the ability to adapt to a rapidly changing industry, ambiguous working environment and shifting project scope.
- Creativity and systems thinking: Exhibited the capacity to integrate knowledge from diverse industries, functions, and technical disciplines to effectively address assigned tasks.
- Curiosity and lifelong learning: Stays updated on trends in AI, enjoys experimenting with current tools and technologies and actively shares knowledge with peers.

Nice to haves or wanting to learn on the job

- Startup or Scaleup experience: Have experience working in a fast-paced startup or scaleup technology business.
- Retail experience: Have experience working in the Retail industry.
- Technical experience: Have experience with AI frameworks such as TensorFlow, PyTorch, and LangChain.

Our culture and core values As we are still in our early stages, we believe cultivating our culture and core values is going to be critical to the success of our business. Our core values are human progress, iterate quickly, further together, be dependable, and have fun. We are looking for individuals who are attracted to these values and wanting to help shape our culture as we grow.

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📌 Senior Engineer (Melbourne)
🏢 Xephyr
📍 Melbourne