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- Tasks: Lead a team to build scalable AI systems and web applications using Python and TypeScript.
- Company: Join a fast-growing AI-native startup backed by strong VC funding, recognised as a top employer.
- Benefits: Enjoy remote work flexibility, access to high-performance compute, and a collaborative environment.
- Why this job: Shape the future of intelligent software while working with cutting-edge AI technology in a supportive culture.
- Qualifications: Strong leadership experience in AI/ML, cloud infrastructure, and production-grade product development required.
- Other info: Opportunity to work closely with research teams and influence engineering culture as the team grows.
The predicted salary is between 43200 - 72000 £ per year.
Better Placed Ltd – A Sunday Times Top 10 Employer! provided pay range This range is provided by Better Placed Ltd – A Sunday Times Top 10 Employer!. Direct message the job poster from Better Placed Ltd – A Sunday Times Top 10 Employer! Director | Co-Founder @ Better Placed Tech + UK AI Meetup. Trusted AI Talent Partner – from disruptive startups to enterprise leaders. Director of Software Engineering – AI Native Start-up UK – Remote My client is a fast-growing AI-native startup focused on building scalable agent-based systems and LLM-powered applications for enterprise customers. Backed by strong VC funding and already working with enterprise organisations, they’re now looking for a Director of Software Engineering to help scale their engineering function in the UK as they move from early traction to broader market adoption. This is a hands-on leadership role where you’ll guide the engineering team in building production-ready AI systems—balancing speed, reliability, and scalability. You’ll work closely with research teams to deploy language models into production, shape technical architecture across cloud infrastructure and application layers, and lead on engineering hiring and culture as the team grows. Lead the design and development of interactive, scalable agent-based systems and web applications using modern languages like Python and TypeScript . Oversee the build and maintenance of server-side APIs and orchestration layers , ensuring smooth integration between frontend apps, backend services, and AI/ML components. Work closely with internal AI research teams to productionise LLMs , focusing on performance, scalability, and reliability . Drive the development of data generation and testing pipelines to ensure the quality and robustness of deployed models. Architect, deploy, and maintain cloud infrastructure (AWS, GCP, or Azure) to support both web applications and machine learning operations (MLOps) . Foster engineering best practices around code quality, testing, documentation, and DevOps . Strong technical leadership experience (Head / Director level), ideally within AI-first or ML-focused product companies . Experience in cloud infrastructure deployment (AWS / GCP / Azure) and containerisation/orchestration (Docker / Kubernetes). Comfortable working with or around machine learning pipelines , even if not directly training models. Experience building and scaling production-grade AI-powered products . Strong collaborator, with a track record of working closely with AI research, product, and infrastructure teams . Bonus Points: Exposure to MLOps , AI observability , or LLM deployment at scale . Experience with data engineering for large-scale pipelines . AI-native mission: Shape the next generation of intelligent, agent-based software products. Access to high-performance compute (dedicated GPU clusters) and modern infrastructure. Collaborative, research-driven environment, blending strong engineering rigour with cutting-edge AI experimentation. Remote-first with optional London hub. Employment type Full-time Job function Information Technology and Engineering Industries Software Development and IT System Custom Software Development Referrals increase your chances of interviewing at Better Placed Ltd – A Sunday Times Top 10 Employer! Get notified about new Director of Software Engineering jobs in London Area, United Kingdom . SVP, Software Engineering Manager – Risk Technology Director of Technology & Engineering – Digital Ecommerce Product Company Director of Data Platforms & Engineering Investment VP / Director / Partner – Software Private Equity Buy-Out – London Director of Software Engineering C++ Trading Engineering Director, GTPN Platform (Relocate to China) Technical Director (Structural Engineering) Engineering Director (Relocation to Prague, CZ) Director of Software Engineering – Credit Real-time Risk We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #
Manager, Software Engineering (ML) employer: Better Placed Ltd - A Sunday Times Top 10 Employer!
Contact Detail:
Better Placed Ltd - A Sunday Times Top 10 Employer! Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Manager, Software Engineering (ML)
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning, especially in relation to scalable agent-based systems. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the AI and software engineering sectors. Attend meetups or webinars related to AI and ML, as this can lead to valuable connections and insights about the company culture at Better Placed Ltd.
✨Tip Number 3
Showcase your leadership experience by discussing specific projects where you led a team in developing AI-powered products. Be prepared to share examples of how you fostered collaboration between engineering and research teams.
✨Tip Number 4
Research the cloud infrastructure tools mentioned in the job description, such as AWS, GCP, or Azure. Being able to speak confidently about your experience with these platforms will set you apart from other candidates.
We think you need these skills to ace Manager, Software Engineering (ML)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in software engineering, particularly with AI and ML technologies. Emphasise your leadership roles and any hands-on experience with Python, TypeScript, and cloud infrastructure.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and your vision for building scalable systems. Mention specific projects or achievements that demonstrate your ability to lead engineering teams and collaborate with research teams.
Showcase Technical Skills: Clearly outline your technical skills related to cloud platforms (AWS, GCP, Azure), containerisation (Docker, Kubernetes), and MLOps. Provide examples of how you've successfully implemented these in previous roles.
Highlight Collaboration Experience: Since the role involves working closely with various teams, include examples of past collaborations with product, research, and infrastructure teams. This will show your ability to foster a collaborative environment.
How to prepare for a job interview at Better Placed Ltd - A Sunday Times Top 10 Employer!
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with modern programming languages like Python and TypeScript. Highlight specific projects where you've built scalable AI systems or worked with cloud infrastructure, as this will demonstrate your hands-on leadership capabilities.
✨Emphasise Collaboration Skills
Since the role involves working closely with AI research teams, be ready to share examples of how you've successfully collaborated with cross-functional teams in the past. This could include instances where you’ve integrated AI/ML components into production systems.
✨Discuss Engineering Best Practices
Talk about your approach to fostering engineering best practices, such as code quality, testing, and documentation. Providing concrete examples of how you've implemented these practices in previous roles can set you apart from other candidates.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in real-world situations. Think about challenges you've faced in deploying AI models or managing cloud infrastructure, and be ready to explain how you overcame them.
