Principal Engineering Lead, AI Enabled Solutions

Kantar Group; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

A leading analytics firm is seeking a Principal Engineering Lead in London to drive AI-enabled solutions. This role requires extensive experience in AI engineering, including MLOps and strong skills in modern backend technologies such as .NET Core and C#. The successful candidate will lead technical teams, ensuring excellence in software practices while fostering a collaborative atmosphere. Familiarity with cloud platforms like Azure and AWS is essential, as well as having a proven record in mentoring and supporting continuous learning within teams.

Qualifications

• Proven experience in AI engineering, including building, deploying, and maintaining ML and generative AI solutions.
• Strong knowledge of MLOps practices for continuous integration, deployment, and monitoring of AI models.
• Deep expertise in Microsoft .NET Core and C#, with ability to code in Python, Go, or TypeScript.

Responsibilities

• Build, enhance, and support AI-enabled solutions.
• Mentor teams and foster a culture of continuous learning.
• Collaborate with diverse teams including Data Science and Product Management.

Skills

AI engineering

MLOps

Microsoft .NET Core

C#

Python

Go

TypeScript

Microservices architecture

SQL databases

NoSQL databases

APIs

Cloud platforms

Containerization

Secure coding practices

Tools

Docker

Kubernetes

Azure

AWS

Google Cloud

Job description

We are looking for a talented **Principal Engineering Lead, AI Enabled Solutions** to join our engineering community, in our offices in London (South Banck Central) or in Porto. 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.