AI Engineer ML, LLM & Agentic AI

ABOUT THE ROLE

Overview

We are looking for an AI Engineer who can build intelligent systems end-to-end, working across Machine

Learning, LLMs, Generative AI, Agentic AI, model development, fine-tuning and production AI systems. This is a

hands-on engineering role: you will take ambiguous problems, determine the right AI approach, build and

evaluate the solution, productionise it and continuously improve it.

The AI Engineer will use AI coding agents such as Claude Code and Cursor to accelerate development, while

owning the correctness, security, reliability and maintainability of everything shipped. This is an individual

contributor role requiring strong ML, LLM and Agentic AI fundamentals, production engineering discipline and

the ability to work independently with ambiguous requirements, and requires 5+ years of relevant experience.

THE WORK

Key Responsibilities

• Own AI initiatives end-to-end, from problem definition and experimentation through development,

evaluation, production and continuous improvement.

• Translate real-world product problems into measurable AI/ML solutions, and determine whether a problem

requires ML, LLMs, RAG, fine-tuning, Agentic AI or a hybrid approach.

• Build, train, evaluate and deploy ML models using modern frameworks such as PyTorch, TensorFlow and

scikit-learn.

• Build production-grade LLM applications, intelligent workflows and Agentic AI systems with planning,

reasoning, tool use and multi-step execution.

• Build RAG pipelines, retrieval systems, embeddings and semantic search using vector stores such as

pgvector, Qdrant, Milvus or Pinecone.

• Implement model fine-tuning and adaptation techniques, including PEFT, LoRA and QLoRA.

• Build evaluation frameworks for ML and LLM-based systems, and optimise for quality, latency, cost and

reliability.

• Build APIs and production services around AI/ML models, and monitor systems in production to

continuously improve performance.

• Deploy and operate AI/ML systems on AWS, Azure or GCP using Docker, Kubernetes and CI/CD pipelines.• Use Claude Code, Cursor and other AI coding agents to increase engineering velocity, reviewing and owning

everything shipped.

WHAT WE'RE LOOKING FOR

Qualifications & Experience

Essential

• 5+ years of experience in AI/ML engineering or a closely related engineering role.

• Strong Machine Learning and Deep Learning fundamentals, with hands-on model development, training,

evaluation and validation experience.

• Strong hands-on experience with LLMs, prompt/context engineering, structured outputs and function/tool

calling.

• Hands-on experience with RAG architectures, embeddings and vector search.

• Hands-on Agentic AI experience, including agent orchestration, planning, tool calling and multi-step

workflow design.

• Experience with model fine-tuning and parameter-efficient techniques such as PEFT, LoRA or QLoRA.

• Strong Python and software engineering fundamentals, with experience building APIs and production

services around AI/ML models.

• Experience with Docker, Kubernetes and cloud deployment on AWS, Azure or GCP.

• Experience with Claude Code, Cursor or equivalent AI development tools.

• Strong problem-solving, system-design and debugging ability, with the ability to work independently with

ambiguous requirements.

Desirable

• Experience building AI products from 0 to 1.

• IoT, energy, industrial or time-series data experience, including forecasting, anomaly detection or predictive

analytics.

• Multimodal AI, open-source model deployment or GPU/inference optimisation experience.

• Experience with AI observability and evaluation, and meaningful open-source contributions or independent

AI projects.