AI & Data Science Engineering Manager – Generative AI / Machine Learning / RAG / Agentic AI / Python

We are currently partnered with a technology organisation working across AI and quantum technologies to deliver advanced solutions for enterprise clients. This opportunity combines technical leadership, project management and hands-on AI expertise, with responsibility for leading international engineering teams and delivering machine learning, computer vision and Generative AI systems into cloud-based production environments.

Key responsibilities

- Lead an international team of engineers to develop and deliver advanced technology solutions for complex industry challenges and client requirements.

- Define the technical direction of complex projects, designing appropriate solutions and ensuring the quality of the technical approach and technologies used.

- Manage projects from initiation through to completion, defining scope, objectives, deliverables, timelines and resource allocation.

- Develop project plans, assess risks and implement contingency plans to address potential challenges.

- Lead, motivate and support cross-functional engineering teams, fostering a collaborative and results-driven environment.

- Monitor project performance and take proactive measures to ensure high-quality delivery.

- Oversee technical documentation, project status reporting and the assessment of documentation quality and accuracy.

- Maintain clear communication with stakeholders, engineering teams and senior management regarding progress, milestones and risks.





- Coordinate cross-project initiatives with other project managers and technical leaders.

- Understand customer objectives and contribute to the development and implementation of business solutions.

- Contribute to technology strategy by providing technical expertise, client insights and recommendations.

- Support the design, implementation and production deployment of machine learning, computer vision and Generative AI systems.

- Collaborate with cross-functional teams to integrate AI models into products and production environments.

Key requirements

- Master’s degree in Computer Science, Data Science, Physics, Engineering or a related field.

- At least 5 years of relevant industry experience.

- At least 2 years of project management experience leading engineering teams within a technology-driven organisation.

- At least 3 years of hands-on industrial experience in data science, Generative AI, deep learning, computer vision, LLMs or software engineering.

- Proven experience designing and implementing ML and AI systems, including Retrieval-Augmented Generation (RAG) and Agentic AI solutions.

- Experience deploying AI systems in cloud-based production environments.

- Experience with LLM fine-tuning and alignment techniques, or model pruning and compression techniques.





- Strong command of Python, Docker and Git.

- Experience with Git Hub or Git Lab workflows and functionality.

- Solid understanding of Agile development methodologies and best practices.

- Strong leadership skills, with the ability to guide and motivate cross-functional teams.

- Excellent communication and interpersonal skills, including the ability to maintain strong client relationships.

- Strong organisational, time-management and attention-to-detail skills.

- Fluent in both Spanish and English.

Keywords

AI Engineering Manager / Data Science Manager / AI Management / Technical Leadership / Engineering Management / Project Management / Artificial Intelligence / AI / Data Science / Quantum Technologies / Generative AI / GenAI / Machine Learning / ML / Deep Learning / Computer Vision / Large Language Models / LLMs / Retrieval-Augmented Generation / RAG / Agentic AI / AI Agents / ML Systems / AI System Design / AI Implementation / Production AI / Cloud-Based Deployment / Model Fine-Tuning / LLM Alignment / Model Compression / Model Pruning / Python / Docker / Git / Git Hub / Git Lab / Agile Development / Software Engineering / International Team Leadership / Cross-Functional Teams / Technical Strategy / Project Planning / Risk Management / Resource Allocation / Stakeholder Management / Client Relationships / Technical Documentation / Spanish / English

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