AI Engineer

Kyberlife; Queenstown; On-site; NZD 100,000 - 130,000; Full time

Job summary

Kyberlife is building the next-generation open marketplace for life sciences, pharmaceuticals, and healthcare product trading. As an AI Engineer, you will help design, build, and maintain AI-powered systems — and the full-stack applications that surround them — to improve how buyers, sellers, and internal teams operate across our marketplace ecosystem.

You will work alongside senior engineers and cross-functional teams to implement machine learning, automation, and generative AI solutions, and

Qualifications

• Solid CS fundamentals with software engineering best practices.
• Proficiency in Python and/or C#, production experience preferred.
• Experience with ML frameworks (PyTorch/TF) and data pipelines.
• Experience deploying AI systems via APIs, containers, and cloud infra.
• Familiarity with LLMs, embeddings, and vector search in production.

Responsibilities

• Build and maintain AI features for buyer experience: search, matching, recommendations.
• Develop ML models for pricing intelligence, demand forecasting, lead scoring, fraud detection.
• Create generative AI components: copilots, automated tools, document summarisation, workflows.
• Develop NLP pipelines for unstructured data: descriptions, catalogs, RFQs, invoices, docs.
• Contribute to CV/OCR pipelines to extract structured data from documents.
• Design backend APIs/services (gRPC) to expose AI features.
• Build frontend dashboards and admin tools (React) for AI features.
• Maintain data pipelines and model-serving infra for training/inference.
• Integrate LLMs, vector databases and retrieval systems into production apps.
• Lead end-to-end feature work with frontend/backend teams when needed.

Skills

Python

C#

ML frameworks

gRPC

REST APIs

Frontend React

AWS cloud

LLMs

Vector search

ETL pipelines

Tools

PyTorch

TensorFlow

scikit-learn

Kubernetes

Job description

Job Description

Kyberlife is building the next-generation open marketplace for life sciences, pharmaceuticals, and healthcare product trading. As an AI Engineer, you will help design, build, and maintain AI-powered systems — and the full-stack applications that surround them — to improve how buyers, sellers, and internal teams operate across our marketplace ecosystem.

You will work alongside senior engineers and cross-functional teams to implement machine learning, automation, and generative AI solutions, and to build the backend services and user-facing interfaces needed to ship them as real product features. This includes contributing to intelligent search, recommendation systems, document understanding, workflow automation, and generative AI applications — end to end, from data pipeline to API to UI.

We are looking for engineers who combine solid software engineering fundamentals with a practical, hands-on approach to AI, and who are comfortable working across the stack — from model or pipeline code, through backend APIs, to the frontend surfaces that expose them to users.

What you will be doing

• Build and maintain AI features that support the buyer experience, such as product search, semantic matching, recommendations, and quotation assistance — including the UI components users interact with.
• Help develop and improve machine learning models for use cases like pricing intelligence, demand forecasting, lead scoring, and fraud detection.
• Build generative AI components such as internal copilots, automated support tools, document summarisation, and workflow assistants — typically under the guidance of a senior engineer or tech lead for the trickier design calls.
• Build NLP pipelines to process unstructured data such as product descriptions, supplier catalogues, RFQs, invoices, certifications, and regulatory documents.
• Contribute to computer vision or OCR pipelines for extracting structured information from uploaded documents and scanned files.
• Design and build backend APIs and services (gRPC) that expose AI features to internal tools and customer-facing products.
• Build and maintain frontend interfaces — dashboards, admin tools, chat/copilot UIs, and internal review or annotation tools — using modern frameworks (e.g., React).
• Build and maintain data pipelines and support model-serving infrastructure for training and real-time inference.
• Integrate LLMs, vector databases, and retrieval systems into production applications, following established patterns and best practices.
• Own a feature end to end where needed — from data/model work, through the API layer, to a working UI — coordinating with dedicated frontend/backend engineers on larger efforts.
• Work with product, operations, and commercial teams to understand requirements and prototype solutions for AI opportunities.
• Follow and help refine team practices for model evaluation, observability, monitoring, and continuous improvement.

Preferred Qualifications

• Solid computer science fundamentals — algorithms, data structures, and software engineering best practices.
• Programming experience in Python and/or C#, ideally with some production software development experience.
• Working knowledge of ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Comfort building and consuming gRPC/REST APIs, and basic familiarity with a modern frontend framework (React, Vue, or similar).
• Some experience deploying AI systems into production using APIs, containers, and cloud infrastructure.
• Familiarity with LLMs, prompt engineering, RAG architectures, embeddings, and vector search — hands-on project experience is a plus, production experience not required.
• Understanding of data pipelines, ETL processes, and relational/non-relational databases.
• Exposure to AWS Cloud and containerized deployments (Kubernetes experience is a plus, not required).
• Awareness of MLOps practices such as CI/CD, experiment tracking, and model versioning.
• Ability to break down a scoped business problem into a workable technical solution, spanning both the AI/data layer and the application layer.
• Good communication skills in English and comfort working cross-functionally.