Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead a dynamic team in delivering cutting-edge AI solutions and software.
- Company: Join a mission-driven company focused on empowering businesses with AI technology.
- Benefits: Enjoy flexible work options, professional development opportunities, and a supportive team culture.
- Why this job: Be at the forefront of AI innovation while mentoring the next generation of engineers.
- Qualifications: 7+ years in software engineering, with leadership experience and a strong technical background.
- Other info: We value diversity and strive for an inclusive workplace for all.
The predicted salary is between 54000 - 84000 £ per year.
Our mission is to build powerful AI agents that help businesses thrive.
We are looking for an experienced Engineering Manager to lead a multidisciplinary team responsible for the full engineering pipeline—spanning front-end, back-end, and AI development. You’ll oversee the delivery of high-quality software and AI solutions while ensuring best practices are followed throughout the engineering lifecycle.
As an Engineering Manager, you will guide technical execution, mentor engineers, and work closely with cross-functional teams to ensure we meet our ambitious goals.
- Technical Leadership: Oversee the entire engineering pipeline (front-end, back-end, AI), ensuring effective collaboration and high-quality delivery across all stages of development.
- Code Quality & Best Practices: Conduct code reviews to ensure adherence to best practices, high-quality code standards, and maintainable solutions.
- Mentorship & Team Development: Lead, mentor, and grow a team of engineers by providing technical guidance, feedback, and support for personal and professional development.
- Ensure that the technical architecture of systems across front-end, back-end, and AI layers is scalable, maintainable, and well-integrated.
- Promote best practices in software engineering and AI development, driving initiatives around code quality, testing, and overall process improvements to optimize development workflows.
- Performance Management: Track and report on team performance, progress, and project timelines, ensuring timely delivery while maintaining high standards of technical excellence.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- 7+ years of experience in software engineering, with at least 2 years in a leadership or managerial role.
- Solid experience across the full engineering stack (front-end, back-end, and AI), with hands-on technical expertise in both.
- Proven experience in code reviews, ensuring adherence to best practices, and helping teams maintain high-quality standards.
- Strong understanding of software engineering principles, design patterns, and architectural best practices.
- Demonstrated experience in removing technical roadblocks and helping teams overcome complex challenges in a fast-paced environment.
- Experience with Agile or Scrum methodologies and leading engineering teams in these frameworks.
- Master’s degree in Computer Science, AI, Engineering, or a related field.
- Extensive experience with Generative AI technologies, including large language models (LLMs) and natural language processing (NLP).
- Familiarity with cloud platforms (AWS, Azure, GCP) and distributed systems.
- Strong leadership skills with a track record of developing high-performing engineering teams.
We embrace diversity and are committed to creating an inclusive environment for all employees.
Engineering Project Manager (field based) employer: AI71
Contact Detail:
AI71 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineering Project Manager (field based)
✨Tip Number 1
Familiarise yourself with the latest trends in Generative AI and cloud technologies. Being well-versed in these areas will not only boost your confidence during discussions but also demonstrate your commitment to staying current in a rapidly evolving field.
✨Tip Number 2
Network with professionals in the engineering and AI sectors, especially those who have experience in leadership roles. Engaging with them can provide valuable insights into the role and may even lead to referrals or recommendations.
✨Tip Number 3
Prepare to discuss your experience with Agile methodologies and how you've successfully led teams in fast-paced environments. Be ready to share specific examples of overcoming challenges and driving team performance.
✨Tip Number 4
Showcase your mentorship skills by thinking of ways you’ve helped others grow in their careers. Highlighting your ability to develop high-performing teams will resonate well with us as we value leadership and team development.
We think you need these skills to ace Engineering Project Manager (field based)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in software engineering and leadership roles. Emphasise your hands-on expertise across the full engineering stack, particularly in AI development, as this is crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI technologies and your vision for leading a multidisciplinary team. Mention specific examples of how you've successfully managed projects and mentored engineers in the past.
Showcase Technical Skills: Include a section in your application that outlines your technical skills, especially in Generative AI, cloud platforms, and Agile methodologies. This will demonstrate your fit for the technical leadership aspect of the role.
Highlight Leadership Experience: Detail your experience in leading teams and managing performance. Provide examples of how you've removed technical roadblocks and driven process improvements to optimise workflows, as these are key responsibilities of the position.
How to prepare for a job interview at AI71
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with the full engineering stack, especially in front-end, back-end, and AI development. Highlight specific projects where you led technical execution and overcame challenges.
✨Demonstrate Leadership Skills
Share examples of how you've mentored engineers and fostered team development. Discuss your approach to performance management and how you've helped teams achieve their goals in a fast-paced environment.
✨Emphasise Code Quality and Best Practices
Prepare to talk about your experience with code reviews and maintaining high-quality standards. Be ready to explain how you promote best practices in software engineering and AI development within your teams.
✨Familiarity with Agile Methodologies
Discuss your experience with Agile or Scrum methodologies and how you've successfully led engineering teams using these frameworks. Provide examples of how these practices have improved project delivery and team collaboration.
