Principal Engineering Lead, AI Enabled Solutions

Kantar Australia; City of London; On-site; GBP 80,000 - 120,000; Full time

Job summary

A leading analytics firm seeks a Principal Engineering Lead to spearhead the development of AI-enabled solutions. The role requires deep expertise in AI engineering, MLOps, and software architecture. Ideal candidates will have 2–4 years in a technical lead role and a passion for mentoring teams. This position offers an opportunity to work with cutting-edge technology, fostering a culture of learning and innovation.

Qualifications

• 2–4 years in a principal engineer or software architect role.
• Proven success mentoring teams and fostering continuous learning.
• Ability to translate complex AI concepts for stakeholders.

Responsibilities

• Build, enhance, and support our AI-enabled platform.
• Deploy and maintain machine learning and generative AI solutions.
• Collaborate with diverse teams including Data Science and Product Management.

Skills

Proven experience in AI engineering

Strong knowledge of MLOps practices

Deep expertise in Microsoft .NET Core

Understanding of microservices architecture

Experience deploying on Azure, AWS, or Google Cloud

Secure coding practices

Strong communication skills

Tools

Docker

Kubernetes

SQL databases

NoSQL databases

Job description

We are looking for a talented **Principal Engineering Lead, AI Enabled Solutions** to join our engineering community. Together we are building, enhancing and supporting the next generation of our platform. This role is perfect for a highly experienced software engineer or software architect who loves to work as a team whilst building elegant and simple solutions that scale.* Proven experience in AI engineering, including building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, RAG, vector search, model fine-tuning).* Strong knowledge of MLOps practices for continuous integration, deployment, and monitoring of ML/AI models.* Experience with AI-specific infrastructure, such as model orchestration pipelines, GPU-based compute, and AI model hosting services.* Understanding of vector databases, semantic search, and scalable data structures for AI applications.* Familiarity with AI governance, responsible AI principles, and model evaluation techniques.* Deep expertise in Microsoft .NET Core, C#, and modern back-end technologies, with the ability to code across multiple languages such as Python, Go, or TypeScript.* Strong understanding of microservices architecture, distributed systems, and cloud-native design patterns.* Experience with SQL databases (e.g., Microsoft SQL Server, PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, CosmosDB).* Proficiency in synchronous and asynchronous APIs, messaging frameworks, and event-driven systems.* Secure coding practices with a strong grasp of cybersecurity threats, especially in the context of AI and data privacy.* Experience deploying large-scale AI and software solutions on Azure, AWS, or Google Cloud.* Familiarity with containerization and orchestration (Docker, Kubernetes).* Knowledge of cloud-native data pipelines and serverless computing environments.* 2–4 years in a principal engineer, technical lead, or software architect role, demonstrating strong technical leadership in both AI and software engineering.* Experience mentoring teams and fostering a culture of continuous learning and technical excellence.* Ability to translate complex AI concepts into actionable strategies for technical and business stakeholders.* Strong communication skills with proven success collaborating across diverse teams, including Data Science and Product Management.