At a Glance
- Tasks: Design and deliver scalable AI solutions while solving complex engineering challenges.
- Company: Join a leading tech firm in Central London with a hybrid work model.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
- Other info: Collaborative environment with strong focus on mentorship and career development.
- Why this job: Make a real impact in the AI field and work with cutting-edge technologies.
- Qualifications: Experience in software engineering and building production AI systems is essential.
The predicted salary is between 80000 - 100000 £ per year.
Key Responsibilities
- Technical Design & Delivery
- Contribute to the technical design and architecture of scalable AI solutions.
- Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements.
- Participate in technical design reviews and support architectural decisions for complex AI initiatives.
- Help implement responsible AI, model governance, and production machine learning practices.
- Work with technical and product stakeholders to translate business requirements into practical AI solutions.
- Provide technical insights and feasibility assessments to support product and engineering decisions.
- Technical Expertise & Execution
- Solve complex AI engineering challenges and provide technical guidance to other engineers.
- Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use.
- Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices.
- Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies.
- Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes.
- Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes.
- Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems.
- Contribute to engineering best practices, coding standards, and quality benchmarks for AI development.
- Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation.
- Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing.
- Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance.
- Promote maintainable, observable, secure, and well-tested approaches to AI engineering.
- Cross-functional Collaboration
- Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively.
- Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements.
- Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders.
- Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services.
- Skills, Knowledge and Expertise
- Software engineering experience, including building production AI, Generative AI, or RAG systems.
- Strong experience designing, building, deploying, and maintaining AI systems in production environments.
- Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact.
- Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques.
- Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation.
- Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code.
- Production experience with AWS cloud services and containerised environments, including Kubernetes.
- Experience building reliable APIs, services, and integration patterns for AI-enabled applications.
- Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition.
- Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation.
- Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams.
- Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation.
- Nice to Have
- Experience with model fine-tuning, RLHF, or custom training approaches.
- Familiarity with MLOps platforms and experiment-tracking tools.
- Experience with infrastructure as code, such as Terraform or CloudFormation.
- Experience with LLM evaluation, tracing, prompt management, or AI observability platforms.
- Background in NLP research or contributions to open-source AI or machine learning projects.
Senior AI Engineer in London employer: Robson Bale
As a Senior AI Engineer in Central London, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. The company offers a hybrid working model, competitive benefits, and ample opportunities for professional growth, ensuring that you can make a meaningful impact while advancing your career in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Robson Bale or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Robson Bale.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Robson Bale.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Robson Bale that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior AI Engineer in London
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 Robson Bale.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Robson Bale 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 Robson Bale
✨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 Robson Bale 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.
