Principal Software Engineer (Python, AI) in London

Principal Software Engineer (Python, AI) in London

London Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead AI platform architecture and mentor senior engineers while shaping engineering strategy.
  • Company: Dynamic tech company focused on AI innovation and collaboration.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Join a forward-thinking team with a focus on cutting-edge technology and career advancement.
  • Why this job: Make a significant impact on AI systems and drive architectural decisions across teams.
  • Qualifications: 10+ years in software engineering with strong AWS and AI governance expertise.

The predicted salary is between 63000 - 77000 £ per year.

Here’s a summary of the role: This is a principal-level role for someone who has already operated at Staff or Principal Engineer level in a sizeable engineering organization and can point to specific platform decisions — in production today — that they own. You'll set the technical direction for our AI-enabled platform: architecting secure, scalable, serverless systems on AWS, defining the patterns and governance practices that multiple teams adopt, and guiding where AI genuinely adds value across the stack. Your leverage comes from the systems, architectures, and standards you put in place — not from individual output. You'll mentor senior engineers, lead org-wide design decisions, and be the person other technical leaders turn to when the hard calls need to be made. You'll still write code, but that's not where your impact is measured. If you've led complex platform or AI initiatives at scale, have strong opinions about AI governance in production systems, and want the scope to shape an entire platform's future, this is that role.

Here’s a breakdown of what you’ll do (not all of it, just the important stuff):

  • Shape engineering strategy with broad organizational impact — you'll influence long-term architectural direction across multiple teams and products, not just within your own squad.
  • Drive platform evolution by identifying cross-cutting pain points and leading the design of secure, scalable, reusable solutions built on AWS and modern serverless and microservice patterns.
  • Lead architectural discussions and design reviews where the stakes are real — making clear trade-offs around performance, security, reliability, and maintainability, and getting alignment across teams with competing priorities.
  • Own AI architectural decisions end-to-end: design AI-enabled systems with built-in governance, monitoring, and regulatory readiness baked in from the start, not retrofitted.
  • Define where AI adds genuine value and where it doesn't.
  • Act as the organization's AI thought leader — educate engineering teams on model behaviour, agentic systems, and responsible AI practices, and raise the overall maturity of how we design and deploy AI.
  • Mentor and stretch senior and staff engineers, building technical leadership depth across the organisation and holding a high bar for engineering standards.

These are the essentials you’ll need to get an interview:

  • Principal-level track record at scale.
  • 10+ years of software engineering experience, including at least 3 years' operating at Staff or Principal Engineer level in an organization of 100+ engineers.
  • You've led large, complex platform or AI initiatives where you were the decision-maker, not a contributor.
  • Deep, opinionated AWS platform expertise. You've designed multi-account AWS architectures and made the call on when serverless is the wrong choice.
  • You work fluently with Infrastructure as Code — Terraform or CDK preferred — and have strong views on observability, resilience, and security that you've translated into org-wide patterns.
  • Production AI systems experience. You've shipped AI-enabled systems — RAG pipelines, agentic frameworks, LLM orchestration, or similar — into production and can discuss the architectural decisions, failure modes, and trade-offs involved.
  • AI governance in practice. You've defined and implemented AI governance in real production environments — bias and privacy checks in pipelines, audit-ready monitoring, AI usage policies — not just read about it. This is essential, not a bonus.
  • API design and backend platform delivery. Proven track record designing and shipping RESTful APIs and backend platform components using Node.js/TypeScript.
  • You understand frontend concerns well enough to set API contracts that serve product teams effectively, even if you're not writing React day-to-day.
  • Org-level communication and influence. You can align stakeholders on complex technical decisions, run architecture forums, and mentor other senior technical leaders. You're as comfortable in a board-level conversation as you are in a design review.

Principal Software Engineer (Python, AI) in London employer: Diligent-14787b60

Diligent is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a hybrid work environment in the vibrant city of Greater London. With a strong focus on professional development, employees benefit from ongoing training and growth opportunities, while the collaborative atmosphere encourages innovation and teamwork, making it a rewarding place for those looking to make a significant impact in the SaaS industry.

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Contact Details:

Diligent-14787b60 Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Principal Software Engineer (Python, AI) in London

Join Local Tech Meetups

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Contribute to Open Source Projects

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Tap into Online Developer Communities

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We think you need these skills to ace Principal Software Engineer (Python, AI) in London

Python
AI Architecture
AWS
Serverless Systems
Microservices
Infrastructure as Code (Terraform, CDK)
AI Governance

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Diligent-14787b60.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Diligent-14787b60 and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Diligent-14787b60

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Diligent-14787b60 uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.