Senior GenAI Developer

Summary

We are seeking a highly motivated and technically strong GenAI Developer to join our growing team. The ideal candidate will have a solid foundation in software and machine learning engineering and a passion for turning AI concepts into reliable production-grade systems. This role offers an excellent opportunity to learn and grow within a dynamic and collaborative environment.

The teams portfolio focuses on agentic and LLM-powered applications built on strong data foundations. We take complicated business problems dive deep into the data and processes associated with those problems and create end-to-end generative/agentic solutions: from the data pipelines underneath to the agents retrieval and evaluation on top.

Key Responsibilities

Be a contributor to the end-to-end AI solution. Wrangle the data build the pipelines design the agents and prompts define the parameters of productionization and continuously improve it.

Build and maintain LLM-powered and agentic applications: orchestration tool-use and retrieval-augmented generation (RAG) along with the evaluation and guardrails that keep them reliable.

Have a strong understanding of AI/ML and modern data foundations and be able to advocate for new ideas and changes to the current roadmap. We work closely as a team so communication is key.

Be willing to innovate particularly on complicated undefined problems. We often are given an outcome and it is our job to find the way to take the business there.

Proactive and results-oriented: Embraces challenges with enthusiasm and a positive can-do attitude consistently exceeding expectations.

Innovative and solution-focused: Proactively identifies opportunities for improvement and contributes creative solutions to enhance efficiency and effectiveness.

Customer-centric: Demonstrates a strong understanding of customer needs and leverages this knowledge to deliver exceptional service and build strong relationships.

Analytical and detail-oriented: Meticulously gathers and analyzes information to effectively identify and resolve complex problems.

Collaborative team player: Actively contributes to a positive team environment fostering collaboration and contributing to shared success.

Growth-minded: Actively seeks opportunities to develop new skills and apply them to enhance job performance and contribute to organizational goals.

Critical Qualifications

Bachelors degree in computer science Statistics Mathematics Data Science Engineering or a related field. Relevant experience may be considered in lieu of a degree.

Approximately 36 years of relevant work experience in a software machine learning or AI engineering role.

Experience in a Cloud environment. GCP is preferred but we recognise that cloud skills are transferable.

Proficiency in Python and SQL.

Hands-on experience building with LLMs prompt design RAG and agent frameworks (e.g. Google ADK/LangChain/LangGraph or similar).

Familiarity with building and maintaining data pipelines (e.g. Beam and Dataflow).

Experience with popular machine learning libraries (e.g. scikit-learn TensorFlow PyTorch).

Experience with a major Generative AI platform such as Gemini Enterprise.

Preferred Qualifications

Experience in the telecommunications or media industry or applying technical solutions to operational/business problems.

Experience deploying AI/ML systems to production including monitoring and evaluation (MLOps).