Senior Staff Software Engineer, AI Customer Operations

📍London / UK Remote | 💰 £135,000 - £184,000 + Share Options | Benefits | Technology 

Senior Staff Engineer: L70 on our Engineering Progression Framework

About our Engineering Teams

We have around 450 engineers out of roughly 5,000 people in total - and we have big ambitions. There are many interesting challenges ahead, and we're happy for people to move between teams or to specialise, whatever you prefer. As an engineer here you'd be able to work directly with anyone across the company, and we run regular knowledge-sharing sessions so you’ll learn heaps about everything from how banks work to effective communication.

We contribute to open source software as much as possible. Our blog is a good place to learn even more about what we do.

About Customer Operations

This role sits in our Customer Operations collective. Our Customer Operations team includes over 75 technical staff (Backend Engineers, ML Engineers, Mobile Engineers, Web Engineers, Analytics Engineers, and Data Scientists). 

Our vision is to deliver seamless support that builds trust, deepens loyalty, and powers Monzo’s sustainable, profitable growth. We enable this vision by providing tech-led and human support experiences for over 14 million customers. 

We have three focus areas:

• Automation-first Customer Problem Detection and Resolution. We are committed to an automation-first approach in customer experience, which includes:
  • Proactive issue prevention: Identifying and resolving high-friction issues before they impact customers, with a focus on scalable, systemic solutions.
  • Automated and AI-driven resolution: Delivering high-quality self-service and AI-powered experiences to resolve customer issues. 
  • End-to-end customer resolution: Providing platforms and tools that allow AI to work alongside human specialists to resolve complex customer journeys.
• Automated Workforce Management. We are building an efficient, automated operational model that integrates machine learning for forecasting, scheduling, routing, and task-matching to optimize our global operations.
• Solid Tech Foundations and Developer Experience. Customer Operations operates as a platform providing a highly available, reliable, secure, compliant, and performant platform of data, software, and infrastructure solutions that:
  • meet the needs of our growing business
  • accelerate the productivity of humans in the loop
  • maintain cost-efficiency that is at most linear to the growth of our business

Senior Staff Engineer responsibilities

A Senior Staff Engineer at Monzo is a technical (IC) leadership position. You will have company-wide influence, working with other collectives to grow Monzo.

This role will primarily focus on automation-first customer problem detection and resolution. You’ll sit at the intersection of our customer experience, AI and platform teams to bring customer-focused automation solutions that improve customer satisfaction and product engagement while building a cost-efficient way to scale operations. 

More specifically, you’ll:

• Expect to be hands on and deeply technical with code and infrastructure, using your software engineering and system building skills and expertise to lean in and solve deep technical challenges
• Partner with the Engineering Director for Customer Operations and other ICs to provide technical leadership around resiliency across Monzo
• Build a deep understanding of our customer journeys and infrastructure and then work to strengthen the infrastructure and tooling to build consistent experiences at scale; enhancing the tools, patterns and guardrails that make high-quality customer experience choices the easy ones
• Work collaboratively with product, data and operational leaders to identify and execute on opportunities that further the organisation's goals and strategy, bringing the right level of clarity, urgency and rigour as appropriate.
• Oscillate between contributing to high-level planning and strategy and organisational leadership and diving deep into the execution of problems and getting hands-on as necessary.
• Work on solving multi-faceted optimisation problems at scale, such as how to maximise the leverage of technologies like LLMs, traditional machine learning, and efficient end to end systems.
• Keep a high bar for technical excellence in the collective, through your own work, highlighting the work of others and calling out when things haven't quite met the bar.
• Use your expert knowledge and experience to lead architectural discussions for the most complex systems in the collective. You’ll do this in order to arrive at solutions that are robust and optimal given the context 
• Foster a culture of quality within your collective. Proactively champion measures to test work, and make this easy
• Pro-actively mentor, sponsor and up-level engineers

🤩What we’re looking for…

To succeed in this role, you will need a strong background in both modern platform tooling and practical software development.

• Software engineering foundations. You have significant professional experience in software engineering, demonstrated by writing, testing, and deploying robust backend services using strongly typed languages.
• AI / Co-pilot. You have experience in solving human + tech problems at scale.
• Customer focus with a platform mindset. You are naturally inclined to solve customer problems through a platform mindset that allows solutions to scale across the company.

• System curiosity: You are deeply curious about systems, enjoy diving deep to investigate complex issues, and understand how modern distributed applications fail and scale.
• Comfort with Ambiguity: You're comfortable working in a fast-paced team that deals with ambiguity and evolving requirements.
• Quantitative mindset: You care about outcomes and you make data-informed decisions.

What you’ll be using/ What you’ll be working on: 

We rely heavily on the following tools and technologies:

• Go to write our application code (there’s an excellent interactive Go tutorial here)
• Cassandra for most persistent data storage
• Kafka for our asynchronous message queue
• Kubernetes and Docker to schedule and run our services 
• AWS for most of our production infrastructure and GCP for most of our data infrastructure.
• React for internal Web dashboards
• Feast for storing our features along a variety of tools to train and deploy models.

🤩We’d love to hear from you if… 

• You have a track record of technical excellence, delivering resilient systems, ideally behind consumer products
• You have technically led large teams to solve complex product challenges and manage trade-offs.
• You have experience working on Backend Systems, Data-intensive systems or real-world ML deployments
• You want to be involved in building and protecting a product that you (and over 14 million others) use
• You have a quantitative mindset: you care about outcomes and you make data-informed decisions
• You’re comfortable working in a team that deals with ambiguity and have experience helping your team and partner team resolve that ambiguity 

🙌What’s in it for you

💰£135,000 - £184,000 ➕ share options + benefits

✈️ We’ll help you relocate to the UK.

✅ We can sponsor your visa. 

📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London) 

⏰We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team. 

📚£1,000 learning budget each year to use on books, training courses and conferences.

🏡We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup. 

➕ Plus lots more! Read our full list of benefits.

🌈 The application journey has 4 key steps

Our interview process involves four main stages after an informal recruiter call: 

1. Recruiter Call 
2. Initial Call 
3. System Design Interview 
4. Take home task or pair coding exercise 
5. Final interview including a behavioural and a leadership interview 

This process should take around 3-4 weeks - your schedule is really important to us, so we promise to be as flexible as possible! 

One of our senior staff engineers has written a detailed blog on their experience through this process, for extra details, hints and tips please see here.