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- Tasks: Lead engineering initiatives from concept to production in a fast-paced environment.
- Company: Join a fully remote team focused on AI-native solutions and impactful delivery.
- Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by driving outcomes and leveraging AI tools for efficiency.
- Qualifications: Experience in managing complex systems and a strong execution mindset.
- Other info: Ideal for those who thrive under pressure and value accountability.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for an Engineering Manager who combines strong execution skills with a high sense of ownership. This is not a traditional people-manager role; it’s about driving outcomes, making pragmatic trade-offs, and ensuring delivery in a fast-paced environment.
What you’ll do:
- Own engineering initiatives from concept to production and execute against a high-pressure roadmap.
- Translate product direction into actionable plans and make clear decisions on priorities, scope, and trade-offs.
- Ensure engineering quality, reliability, and pragmatic technical standards while balancing speed and technical debt.
- Identify and remove blockers, streamline processes, and step in hands-on when needed.
- Maintain high standards for team ownership, output, and accountability.
- Work closely with Product as a delivery co-owner and contribute to senior-level strategy discussions.
AI-Native approach:
This role requires an Engineering Manager who is AI-native, not AI-curious. You should:
- Regularly use AI tools to increase personal and team leverage.
- Apply AI to accelerate engineering execution and delivery speed.
- Coach teams on responsible, effective AI usage.
- Demonstrate sound judgment on where AI adds value and where it does not.
The Environment:
- Fully remote team.
- Trade-offs and technical debt are part of day-to-day decisions.
- Outcomes matter more than optics, and timely decisions often outweigh consensus.
- Delivery pressure is real and sustained.
A good fit if you:
- Have owned delivery for complex systems or products.
- Have experience in fast-moving startup or scale-up environments.
- Take accountability for outcomes and make decisions with incomplete information.
- Remove blockers, accelerate delivery, and care about execution quality.
- Use AI tools as a force multiplier for speed, quality, and impact.
Not a fit if you:
- Avoid performance conversations or hard trade-offs.
- Rely heavily on process rather than execution.
Software Engineering Manager employer: Global M
Contact Detail:
Global M Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineering Manager
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in AI or engineering management. A personal referral can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies that highlight your experience with complex systems and AI tools. This will help you demonstrate your hands-on approach and execution quality during interviews.
✨Tip Number 3
Be ready for scenario-based questions! Think about how you would handle trade-offs and blockers in a fast-paced environment. Practising these scenarios will help you articulate your thought process clearly.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Plus, it gives you a chance to showcase your enthusiasm for the role and the company right from the start.
We think you need these skills to ace Software Engineering Manager
Some tips for your application 🫡
Show Your Ownership: When writing your application, make sure to highlight instances where you've taken ownership of projects. We want to see how you've driven outcomes and made tough decisions in fast-paced environments.
Be Pragmatic: In your written application, focus on your ability to make pragmatic trade-offs. Share examples of how you've balanced speed with quality and managed technical debt while still delivering results.
Emphasise AI Experience: Since we're looking for someone who's AI-native, don't forget to mention your experience with AI tools. Tell us how you've used them to enhance execution and delivery speed in your previous roles.
Keep It Clear and Concise: We appreciate clarity! Make sure your application is straightforward and to the point. Avoid jargon and fluff; instead, focus on what really matters—your skills and experiences that align with our needs.
How to prepare for a job interview at Global M
✨Know Your AI Tools
Since the role is AI-native, make sure you’re well-versed in the AI tools relevant to engineering. Be ready to discuss how you've used these tools to enhance execution and delivery speed in your previous roles.
✨Showcase Your Execution Skills
Prepare examples that highlight your ability to drive outcomes and make pragmatic trade-offs. Think of specific projects where you’ve owned delivery from concept to production, and be ready to explain your decision-making process.
✨Emphasise Problem-Solving
This role requires removing blockers and streamlining processes. Come prepared with stories that demonstrate how you’ve tackled challenges in fast-paced environments and how you’ve ensured quality while maintaining speed.
✨Be Ready for Performance Conversations
Since accountability is key, be prepared to discuss how you handle performance conversations and make tough decisions. Show that you’re comfortable with having difficult discussions and prioritising outcomes over consensus.
