AI Platform Engineering Manager | Cloud-Native Leader

JobCubby; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Pension plan

Life insurance

Maternity leave

Paternity leave

Shared parental leave

25 days holiday

Flexible working hours

Cycle-to-work scheme

Electric car scheme

Season ticket loan

Learning materials and courses

Sports and hobby clubs

Snacks and fresh fruit

Job summary

Thought Machine is recruiting an Engineering Manager to lead a team of engineers, shaping the platform roadmap and delivering AI-enabled tooling. You will balance technical leadership with people management, guiding design reviews, and aligning engineering goals with business strategy.

You will work across modern stacks (Kubernetes, AWS/GCP/Azure) and contribute to a culture of learning, autonomy, and impact, while coaching engineers for growth and delivering high-quality platforms.

Qualifications

• 2+ years of engineering management in platform teams.
• Experience with AI tooling and capabilities.
• Experience in cloud-native environments (Kubernetes, cloud providers).
• Strong communication with users and stakeholders; autonomy.
• Proven ability to develop platforms used by engineers.

Responsibilities

• Lead complex technical projects and roadmap delivery.
• Manage a group of engineers and guide career development.
• Balance hands-on coding with management responsibilities.
• Drive technical decisions and platform strategy with stakeholders.
• Foster adoption of best practices and new tools.
• Collaborate closely with senior leadership and users.

Skills

Engineering management

AI tooling

Cloud-native

Kubernetes

Go/Python

Tools

Kubernetes

AWS/GCP/Azure

Go

Python

Job description

Thought Machine is recruiting an Engineering Manager to lead a team of engineers, shaping the platform roadmap and delivering AI-enabled tooling. You will balance technical leadership with people management, guiding design reviews, and aligning engineering goals with business strategy.

You will work across modern stacks (Kubernetes, AWS/GCP/Azure) and contribute to a culture of learning, autonomy, and impact, while coaching engineers for growth and delivering high-quality platforms.