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 and professional growth.
- 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.
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 Slough 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 and continuous learning, this role offers unique opportunities for personal growth and the chance to shape the future of engineering within the organisation. Enjoy a collaborative work culture that values individual contributions and fosters innovation in a dynamic financial services environment.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager in Slough
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those that highlight your experience with AI-augmented engineering practices. This will give potential employers a taste of what you can bring to their team.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to engineering management. Be ready to discuss your hands-on delivery experiences and how you've led teams through complex workstreams.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who take the initiative. Plus, it gives you a better chance to stand out and be noticed by our hiring team.
We think you need these skills to ace Engineering Manager in Slough
Some tips for your application 🫡
Show Your Technical Credibility:Make sure to highlight your technical expertise in your application. We want to see that you’re not just a manager but a principal engineer who can lead by example. Share specific examples of your hands-on experience with AI platforms, .NET applications, and data analytics.
Emphasise Leadership Experience:We’re looking for someone who has navigated the tricky waters of team leadership. In your application, mention your experience managing teams, handling difficult conversations, and fostering a culture of technical excellence. This will show us you’ve got the chops to lead our high-performing squad.
Be Specific About Your Contributions:When detailing your past roles, focus on your individual contributions. We want to know how you’ve been involved in code reviews, architecture decisions, and hands-on delivery. This will help us see your commitment to being an active part of the team, not just a figurehead.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen to join our team at StudySmarter!
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 leadership experience, especially in managing high-performing teams. Think about how you've handled difficult conversations or team conflicts in the past. This will demonstrate your ability to lead while still being technically credible.
✨Demonstrate Your Individual Contribution Mindset
Be ready to talk about your personal contributions to complex workstreams. Share specific instances where you’ve been involved in code reviews, architecture decisions, or hands-on delivery. This will show that you’re not just a manager but also an active participant in the engineering process.
✨Understand AI-Augmented Delivery
Familiarise yourself with agentic development practices and be prepared to discuss how you’ve implemented AI-assisted delivery in your previous roles. Bring examples of how you’ve used AI tools to improve efficiency and free up senior engineers for more complex problems.
