AI Engineer in London

AI Engineer in London

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
Planet

At a Glance

  • Tasks: Own and design AI workflows that enhance business processes and decision-making.
  • Company: Join Planet, a global leader in tech and payments solutions.
  • Benefits: Competitive salary, hybrid work model, and opportunities for career growth.
  • Why this job: Make a real impact with cutting-edge AI technology in a dynamic environment.
  • Qualifications: Strong software engineering skills and experience with AI/ML systems.
  • Other info: Diverse workplace valuing innovation and collaboration.

The predicted salary is between 36000 - 60000 £ per year.

About Planet

Planet is a global provider of integrated technology and payments solutions for retail and hospitality customers. We create great experiences for the millions of people who use our payments, software, and tax-free solutions every minute of every day. Planet empowers its customers to deliver great customer experiences by combining payments and software in ways that drive greater loyalty, increase revenue and save time. Founded over 35 years ago and with our headquarters in London, today we have more than 2,500 employees located across six continents serving our customers in more than 120 markets.

Role overview:

The AI Engineer owns the full lifecycle of AI-driven workflows across the organisation. This role is accountable not only for technical implementation but also for the quality, reliability, and outcomes of AI systems in production. You will design and operate end‑to‑end AI workflows that connect with internal systems, manage model behaviour, ensure decision accuracy, and continuously improve performance through measurement and iteration. This role requires a blend of software engineering excellence, AI systems understanding, and a strong product mindset focused on real‑world impact.

What you will do

  • End-to-End AI Workflow Ownership
    • Design and build production‑grade AI workflows integrated across internal systems (HR, Finance, Ops, CRM, etc.).
    • Implement orchestration logic including triggers, retries, fallbacks, and human‑in‑the‑loop mechanisms.
    • Ensure workflows are reliable, observable, monitored, and auditable.
  • AI & Model Behaviour
    • Develop and maintain AI agents, prompts, retrieval pipelines, and decision logic.
    • Own and monitor model behaviour in production, including: Accuracy and usefulness, Failure modes, Handling of edge cases and ambiguity.
    • Improve model performance using evaluation frameworks, feedback loops, and real usage data.
  • Decision Quality & Outcomes
    • Take accountability for the quality of decisions produced by AI systems, beyond technical execution.
    • Define, track, and report success metrics (e.g., accuracy, resolution rate, time saved).
    • Diagnose situations where systems function technically but deliver suboptimal outcomes.
  • Collaboration & Platform Usage
    • Work closely with Data Engineering to leverage shared platforms: Infrastructure, CI/CD, Data pipelines, Security & governance.
    • Contribute to shared standards, schemas, and best practices for AI systems.

What Success Looks Like

  • AI workflows run reliably in production with minimal manual interventions.
  • Business users trust and rely on AI‑generated outputs.
  • Model behaviour improves consistently over time through structured evaluation.
  • Clear ownership and accountability when issues arise — no gaps.

Who you are

  • Core Skills & Experience
    • Strong software engineering background (Python or similar).
    • Proven experience building production systems (not just prototypes).
    • Hands‑on experience with AI/ML systems (LLMs, classifiers, decision models, etc.).
    • Skilled in API integration and working with distributed systems.
  • AI & Data Expertise
    • Experience designing prompts, retrieval pipelines, or ML inference workflows.
    • Understanding of model evaluation, monitoring, and feedback loops.
    • Comfortable working with structured and unstructured data.
  • Mindset
    • Product‑oriented with a strong focus on outcomes, not just code delivery.
    • Comfortable navigating ambiguity and making pragmatic trade-offs.
    • Practical and grounded in building AI that works reliably in real-world production environments.

Nice to Have

  • Experience with workflow orchestration tools (e.g., Temporal, Airflow, Step Functions).
  • Experience developing internal tools or AI agents.
  • Familiarity with regulated or enterprise environments.
  • Exposure to MLOps or AI evaluation frameworks.

Why Planet:

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need. Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce. We would love to hear from you – Apply now. At Planet, we embrace a hybrid work model, with three days a week in the office. Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.

AI Engineer in London employer: Planet

Planet is an exceptional employer that fosters a dynamic and inclusive work culture, where innovation thrives and employees are empowered to make a real impact. With a strong focus on professional growth, Planet offers ample opportunities for career advancement in the fast-paced technology sector, all while enjoying the benefits of a hybrid work model in the vibrant city of London. Join us to be part of a team that values diversity and is dedicated to delivering outstanding customer experiences through cutting-edge AI solutions.
Planet

Contact Detail:

Planet Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land AI Engineer in London

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Planet. A friendly chat can sometimes lead to opportunities that aren’t even advertised.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects or contributions. Whether it’s GitHub repos or case studies, having tangible evidence of your work can really set you apart.

✨Tip Number 3

Prepare for interviews by understanding Planet’s products and how AI fits into their ecosystem. Tailor your examples to demonstrate how your experience aligns with their needs—this shows you’re genuinely interested!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re keen on being part of the Planet team right from the start.

We think you need these skills to ace AI Engineer in London

Software Engineering
Python
AI/ML Systems
API Integration
Distributed Systems
Prompt Design
Retrieval Pipelines
Model Evaluation
Monitoring
Feedback Loops
Structured Data
Unstructured Data
Workflow Orchestration Tools
MLOps
Decision Logic

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with AI systems and software engineering, and show us how your skills align with what we're looking for at Planet.

Showcase Your Projects: Include specific examples of production systems you've built or worked on. We want to see your hands-on experience with AI/ML systems, so don't hold back on sharing those impressive projects!

Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to describe your skills and experiences, and make sure we can easily see how you fit into our team and culture.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen to join Planet!

How to prepare for a job interview at Planet

✨Know Your AI Stuff

Make sure you brush up on your knowledge of AI systems, especially the ones mentioned in the job description like LLMs and classifiers. Be ready to discuss your hands-on experience with these technologies and how you've implemented them in production environments.

✨Showcase Your Software Skills

Since a strong software engineering background is crucial, prepare to talk about your experience with Python or similar languages. Bring examples of production systems you've built, focusing on the challenges you faced and how you overcame them.

✨Understand the Business Impact

This role is all about real-world outcomes, so be prepared to discuss how your AI solutions have driven business value. Think about metrics like accuracy and resolution rates, and be ready to explain how you've tracked and improved these in past projects.

✨Collaboration is Key

Planet values teamwork, so highlight your experience working with cross-functional teams, especially with Data Engineering. Discuss how you've contributed to shared standards and best practices, and be ready to share examples of successful collaborations.

AI Engineer in London
Planet
Location: London

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