Lead Data & AI Platform Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Oversee the design and advancement of scalable data, analytics, and AI platforms that bolster customer operations, automation, and operational intelligence on a global scale.

• Design and enhance Databricks-based data pipelines and enterprise data platforms that integrate customer, operational, workforce, and AI datasets.

• Propel machine learning, NLP, Generative AI, and operational intelligence functions to enhance customer experience, operational efficiency, and automation outcomes.

• Provide actionable insights and high-level reporting to support strategic decision-making and operational enhancements.

• Establish engineering standards, governance frameworks, and best practices for data integrity, platform reliability, CI/CD, and AI lifecycle management.

• Collaborate with Product, Operations, Engineering, Workforce Management, and AI teams to ensure alignment of technology investments with business goals.

• Offer technical leadership, mentoring, and daily support to engineers and data scientists.

• Independently manage complex projects and initiatives amidst competing priorities and organizational visibility.

⛳️ Requirements

• Extensive experience in designing scalable data platforms, enterprise data architectures, and operational intelligence solutions based on Databricks.

• Demonstrated experience as a Data Engineer, Analytics Engineer, Data Scientist, Machine Learning Engineer, AI Engineer, or in a similar technical leadership position.

• Proficient in Databricks, Spark, cloud data platforms, and large-scale data pipelines.

• Experience in developing AI/ML solutions utilizing Python and contemporary data science frameworks.

• Strong foundation in statistics, machine learning, NLP, forecasting, and operational analytics.

• In-depth knowledge of conversational AI ecosystems, intent modeling, NLU analytics, and AI performance assessment.

• Familiarity with implementing CI/CD frameworks, version control, automated testing, and DevOps best practices.

• Proven experience in creating scalable dashboards and reporting solutions using BI tools and modern visualization frameworks.

• Capacity to independently manage complex initiatives with competing priorities and high organizational visibility.

• Excellent communication, stakeholder management, and problem-solving abilities.

• Experience with Generative AI, LLM orchestration, prompt engineering, or AI-assisted automation workflows.

• Knowledge of Kubernetes, Docker, GitLab CI/CD, and contemporary ML deployment frameworks.

• Experience in supporting global or enterprise-level customer operations environments.

• Familiarity with contact center platforms such as Zendesk, Five9, Amelia, or conversational AI tooling ecosystems.

🏝️ Benefits

• Inclusive work environment

• Support to balance work and home life

• Professional and personal development opportunities

• Opportunities to gain new experiences and learn from skilled colleagues

• Equal opportunity employment

• Human review of AI-supported application screening and assessment