At a Glance
- Tasks: Lead a high-performing team to transition engineering capabilities in-house using AI-augmented practices.
- Company: Leading buy-side investment client in London with a focus on innovation.
- Benefits: Competitive contract salary and the chance to shape engineering culture.
- Other info: Dynamic role with opportunities for personal growth and team mentorship.
- Why this job: Make a real impact by reshaping software delivery with cutting-edge AI technology.
- Qualifications: Proven technical leadership, hands-on coding experience, and expertise in AI and .NET applications.
The predicted salary is between 80000 - 100000 £ per year.
We are looking for an Engineering Manager on a contract basis for a leading buy side Investment client in London. The Engineering Manager will lead a critical transition from external delivery dependency to in-house engineering capability — with a unique twist: you'll reshape how the entire team delivers software using AI-augmented engineering practices. This is a principal engineer who manages, not a manager who codes occasionally. You'll carry real individual contribution (code reviews, architecture decisions, hands-on delivery on complex workstreams) alongside leading a small, high-performing in-house squad and stewarding relationships with external resources.
WHAT YOU'LL OWN
- Technical Leadership & Strategy
- Architecture ownership across three technical domains: AI platform, proprietary .NET applications (core business systems), and data/analytics/reporting infrastructure
- Individual contribution on complex technical workstreams — code reviews, architecture decisions, hands-on delivery alongside your team
- Set technical standards, code-quality bar, and delivery cadence for in-house engineering
- Define the AI-augmented delivery model: how your team uses agentic development tooling, spec-driven approaches, and LLM-assisted pipelines to punch well above its weight
- Team Leadership
- Direct leadership of small, senior in-house engineering squad
- Set hiring strategy, onboarding, growth, and technical mentorship
- Foster culture of technical excellence, ownership, and continuous learning
- Manage performance, development, and retention of core team
- External Resource Management
- Steward relationships with external development partner during knowledge-transfer phase
- Transition workload progressively from external to in-house delivery
- Maintain quality and momentum while shifting capability in-house
- Define SLAs, delivery expectations, and handoff protocols
- Knowledge Absorption & Transition
- Reverse-engineer understanding of proprietary systems, architectural patterns, and business domain knowledge from external partner
- Document critical systems, business logic, and technical decisions
- Build durable, maintainable in-house codebase that doesn't perpetuate external partner's patterns
- Plan and execute phased transition from external dependency to self-sufficient in-house delivery
- AI-Augmented Delivery Model
- Design and implement agentic development practices: code generation, testing, documentation automation
- Evaluate Claude Code, agentic pipelines, and spec-driven approaches for your specific context
- Build evaluation frameworks and quality gates for AI-assisted delivery
- Create proof-of-concepts showing how AI tooling reduces routine work and frees senior engineers for high-value problems
- Progressively shift external partner's routine work to AI-assisted in-house delivery
WHAT WE'RE LOOKING FOR
- You are a principal engineer first, manager second.
- 2 plus years of people leadership experience — enough to have handled the hard moments (difficult conversations, performance management, team conflicts), but recent enough that your instincts are still primarily technical
- Strong technical credibility — engineers trust your judgment because you know the work
- Individual contribution mindset — you code, review, architect, and deliver alongside your team, not from the sidelines
- Hands-on delivery track record — comfortable owning complex workstreams end-to-end
Technical Requirements:
- Credible across three domains (deep expertise in one or two sufficient):
- AI Platform & LLM Integration — Building with Claude, OpenAI, agentic systems, RAG, or similar
- Application Engineering (.NET) — Hands-on experience with C#/.NET, microservices, cloud deployment, or application modernization
- Data/Analytics/Reporting — SQL, ETL/ELT, analytics platforms, or data pipeline architecture
- Required:
- Python or TypeScript (primary languages for AI-augmented delivery)
- SQL and relational databases
- Cloud platforms (Azure, AWS, or GCP)
- API design and integration patterns
- Experience shipping production systems in financial services preferred
- AI-Augmented Delivery Vision
- Clear perspective on agentic development tooling — not just hype, but genuine experience with how Claude Code, code generation, and AI-assisted testing actually work in practice
- Understanding of spec-driven approaches — ability to write executable specifications that feed AI-assisted pipelines
- Track record with small, high-performing teams — you've made a small group punch above its weight
- Build-over-buy mindset — bias toward in-house ownership of critical capability
- Practical about AI — knows where AI tooling helps (boilerplate, testing, documentation) and where human judgment still matters (architecture, edge cases, security)
Engineering Manager in London employer: McCabe & Barton
Join a leading buy-side investment client in London as an Engineering Manager, where you'll not only lead a high-performing in-house engineering squad but also play a pivotal role in transforming software delivery through AI-augmented practices. With a strong emphasis on technical excellence, continuous learning, and individual contribution, this role offers a unique opportunity to shape the future of engineering while enjoying a collaborative work culture that prioritises employee growth and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AI-augmented engineering practices. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and leadership scenarios. Be ready to discuss how you've handled complex workstreams and fostered team culture. Practice makes perfect!
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Engineering Manager in London
Some tips for your application 🫡
Show Your Technical Credibility:Make sure to highlight your technical skills and experiences that align with the role. We want to see how you've led teams and contributed to complex projects, so don’t hold back on showcasing your hands-on delivery track record!
Tailor Your Application:Take a moment to customise your application for this specific role. Use keywords from the job description to demonstrate that you understand what we’re looking for in an Engineering Manager. This shows us you’re genuinely interested and have done your homework!
Emphasise Leadership Experience:Since this role requires people leadership, share examples of how you've managed teams, handled tough conversations, and fostered a culture of excellence. We want to know how you’ve helped your team grow and succeed!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for both of us!
How to prepare for a job interview at McCabe & Barton
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical requirements listed in the job description. Brush up on your knowledge of AI platforms, .NET applications, and data analytics. Be ready to discuss your hands-on experience with Python or TypeScript, as well as your familiarity with cloud platforms like Azure or AWS.
✨Showcase Your Leadership Skills
Prepare examples that highlight your people leadership experience. Think about times you've handled difficult conversations or managed team conflicts. The interviewers will want to see that you can lead a high-performing team while still being technically credible.
✨Demonstrate Your Individual Contribution Mindset
Be ready to talk about your individual contributions to past projects. Share specific instances where you’ve been involved in code reviews, architecture decisions, or hands-on delivery. This role requires a principal engineer who actively participates, so make sure to convey your commitment to coding alongside your team.
✨Prepare for AI-Augmented Delivery Discussions
Since this role involves defining an AI-augmented delivery model, be prepared to discuss your understanding of agentic development practices. Bring examples of how you've used AI tools in your previous work, and be ready to share your thoughts on where AI can genuinely add value in software delivery.
