About the role This is a great opportunity for a Senior Software Engineer to join a newly formed AI capability within Seequent Evo — our geoscience data platform used by earth scientists and engineers globally. In this role, you’ll help build and deliver applied Generative AI (Gen AI) solutions, influencing how Gen AI is built into the platform and operated at scale. The systems you deliver will help customers surface insights from their data, simplify workflows, and make informed decisions. You’ll also play a key role in shaping this emerging team as it develops over the coming year. In this role, you will have the opportunity to: Design and architect GenAI solutions using appropriate modelling techniques and agreed engineering standards. Produce and communicate design views that address stakeholder needs and meet functional and non-functional requirements, including security. Identify design trade-offs, evaluate alternatives, and prototype or model behaviours to secure stakeholder alignment. Build, test, document, and maintain complex software and integration services; refactor and improve codebase quality over time. Advocate for effective engineering tools, techniques, and ways of working; monitor and improve adherence to standards (including software security). Lead reviews of colleagues’ designs and code; provide technical mentorship and guidance across the team. Plan and coordinate release activities across teams, ensuring quality, security, and compliance standards are met; lead post-release reviews. Deliver small projects/sub-projects end-to-end: scope, schedule, risk, stakeholder alignment, governance, and outcome tracking. Contribute to building the new team as we hire and scale. To be successful in this role, you should have: Bachelor’s degree in computer science, engineering, or equivalent. 7+ years working in relevant Software Engineering roles. 1+ years building and operating Gen AI products using LLMs in production environments. Experience with and ability to strategize about: Retrieval-Augmented Generation (RAG) systems, semantic search and vector databases, and how to optimize knowledge retrieval for better results MCP (Model Context Protocol), A2A (Agent2Agent Protocol) and/or similar frameworks for exposing services to agentic applications. Familiarity with developing cloud services, particularly experience with Docker, Kubernetes, FastAPI a bonus. Familiarity with CI/CD Pipelines and DevOps practices. Strong stakeholder communication, the ability to work autonomously, and confidence mentoring others and driving good engineering practices. Additional information Office-based working environment, work from our Christchurch office three or more days per week. #LI-NP1