Principal Engineering Lead driving Kantar’s AI technology transformation through scalable solutions. Collaborating with teams for AI projects while mentoring engineers to foster innovation.
Responsibilities
Architecting and delivering scalable AI solutions
Leading the technical direction of AI projects
Mentoring engineers and fostering innovation within the team
Collaborating with Data Science, Product Management, and wider technology groups to translate complex AI concepts into actionable business strategies
Requirements
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.
Experience with UI development technologies such as Angular, TypeScript, JavaScript, HTML5, and modern frameworks to build AI-driven user interfaces.
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