At a Glance
- Tasks: Lead the design and deployment of cutting-edge AI systems and features.
- Company: Join a forward-thinking tech company revolutionising business planning with AI.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with exciting projects and career advancement opportunities.
- Why this job: Make a real impact by building innovative AI solutions that empower users.
- Qualifications: Extensive experience in AI, ML, and strong software engineering skills required.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains.
- End-to-end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience in fine-tuning LLMs for domain-specific enterprise applications.
- Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices (testing, code review, CI/CD).
- Proven track record of delivering complex technical projects on time with high quality.
- (Desirable) Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field.
- (Desirable) Hands-on experience with cloud-native ML infrastructure platforms.
- (Desirable) Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models.
- (Desirable) Experience with model serving frameworks (vLLM, TensorRT, Ray).
- (Desirable) Experience with A/B testing and experimentation frameworks for AI features.
- (Desirable) Contributions to open-source ML projects or research publications.
- (Desirable) Experience with model observability tools (LangSmith, W&B, MLflow).
What the job involves
- We're seeking a Principal Engineer, AI who can work across the full stack of Anaplan AI applications, from model integration and prompt engineering to building intuitive user interfaces.
- You’ll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.
- Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments.
- Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments.
- Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation.
- Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language.
- Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics.
- Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations.
- Optimise model inference pipelines for performance, cost, and scalability in production environments.
- Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour.
- Collaborate with data scientists to productionise ML models and forecasting algorithms.
Principal Engineer (A.I.) in London employer: Anaplan
At Anaplan, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of Artificial Intelligence. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work on cutting-edge projects that have a real impact on business planning. Located in a vibrant tech hub, we provide a stimulating environment where talented individuals can thrive and contribute to meaningful advancements in AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Engineer (A.I.) 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 Anaplan 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 Anaplan.
✨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 Anaplan.
✨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 Anaplan 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 Principal Engineer (A.I.) 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 Anaplan.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Anaplan 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 Anaplan
✨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 Anaplan 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.
