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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Engineering Manager (Python) - AI/ML SaaS Platform - **Company:** Creo Recruitment - **Location:** Manchester, UK - **Experience:** Expert - **Salary:** £120,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Big Data, Software as a Service, Cloud Engineering, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, SQL Databases, Software Technical Review, Parquet, Reliability of Systems, Data Pipelines - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815249058-engineering-manager-python-aiml-saas-platform ## About the Role * Prior experience as an Engineering Manager or Tech Lead managing small, high-performing engineering teams. * Strong technical background in Python, large-scale data systems, and cloud-native architectures (ideally AWS). * Experience owning and improving complex data pipelines and high-throughput systems. * Ability to coach engineers across multiple levels while maintaining hands-on architectural and design credibility. * Excellent delivery management - simplifying ambiguity, unblocking dependencies, and driving predictable execution., * Your squad of 4 consistently delivers high-quality software and scalable data pipelines with predictable velocity. * Clear improvements in system reliability, throughput, and cost efficiency. * Strong engineering discipline across design, testing, observability, and incident management. * Improved technical foundations and reduced operational toil. * Clear, thoughtful communication and alignment across engineering, product, and design. ## Description Engineering Manager (Python) - AI/ML SaaS Platform Base pay range Engineering Manager - London OR Manchester - Salary up to £120k We're hiring a Hands-On Engineering Manager with deep technical leadership experience across Python, large-scale data systems, and modern AWS infrastructure. You'll lead a squad of 4 engineers, guiding them through complex technical decisions and helping them deliver high-performance, data-intensive systems operating over hundreds of millions to billions of rows. The product itself is an AI/ML-driven SaaS platform, and your contributions will train new models, enabling new features and having large greenfield elements to it. This role blends hands-on technical context with people leadership, delivery focus, and architectural oversight. You'll drive engineering excellence, ensure high reliability, and cultivate a culture that values clarity, ownership, and strong execution. What You'll Be Doing * Lead and develop a squad of 4 engineers, supporting growth, coaching, and high-quality delivery. * Set technical direction across Python services, distributed systems, and large-scale data processing. * Work heavily with AWS - especially Redshift, Lambda, ECS, S3, plus data formats like Parquet. * Shape high-throughput data pipelines and SQL-based workflows, ensuring scalability and performance. * Run technical design reviews, guide architecture decisions, and support engineers in navigating trade-offs around performance, cost, and reliability. * Champion operational excellence - strong observability, testing discipline, incident response, and SLO ownership. * Collaborate with Product & Design to define technical requirements, prioritise road-maps, and drive measurable outcomes. Tech Environment You'll Influence * Primary language: Python * AWS stack: Redshift, Lambda, ECS, S3 * Scale: systems processing hundreds of millions to billions of rows * Focus areas: performance tuning, reliability, cost optimisation, architectural clarity What You'll Bring * Prior experience as an Engineering Manager or Tech Lead managing small, high-performing engineering teams. * Strong technical background in Python, large-scale data systems, and cloud-native architectures (ideally AWS). * Experience owning and improving complex data pipelines and high-throughput systems. * Ability to coach engineers across multiple levels while maintaining hands-on architectural and design credibility. * Excellent delivery management - simplifying ambiguity, unblocking dependencies, and driving predictable execution. What Success Looks Like * Your squad of 4 consistently delivers high-quality software and scalable data pipelines with predictable velocity. * Clear improvements in system reliability, throughput, and cost efficiency. * Strong engineering discipline across design, testing, observability, and incident management. * Improved technical foundations and reduced operational toil. * Clear, thoughtful communication and alignment across engineering, product, and design. 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