AI Engineer

gradient-labs· Technology
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🌍 Remote📍 London OfficeFullTime

About this role

AI Engineer

At Gradient Labs, we’re on a mission to make exceptional customer service the norm.

Founded in 2023, we’ve quickly gone from an idea to a growing team with customers you know (and probably love). Our AI agent helps businesses handle even the trickiest, high-stakes customer support queries safely and effectively, all while giving them the visibility and control they need to trust the outcomes.

We’re a small but mighty team of builders from leading companies like Monzo, Pleo, and Google. We work in a hybrid model from our London office, a short walk from Liverpool Street Station, where we collaborate and connect 2-3 days a week.

If you’re excited to tackle some of the hardest problems in AI and help shape the future of customer operations, we’d love to hear from you.

🎯 How you’ll make an impact

This is a build-and-ship role. You'll turn ambiguous customer support problems into reliable, observable AI agents that handle live conversations for real users. You'll work close to production — designing prompts and tool flows, building eval suites, shipping changes, watching what breaks, and iterating fast.

  • Build and operate AI agents in production: Design, implement, and maintain agentic systems powered by LLMs — handling tool calling, multi-step reasoning, and integration with customer APIs and data sources. You'll own these systems end-to-end: reliable, observable, and auditable from day one.

  • Translate business problems into agentic workflows: Work directly with enterprise customers to understand their workflows, surface the highest-leverage automation opportunities, and frame them as well-scoped agent problems with clear success criteria. You'll be the technical counterpart in customer conversations, turning ambiguity into a concrete plan.

  • Build robust evaluation infrastructure: Create and maintain eval suites drawn from real-world scenarios and edge cases. Go beyond vibes-based testing: structured evals measuring accuracy, safety, and latency, tied to clear business outcomes, used to drive systematic improvements to prompts, tools, and behaviour.

  • Enhance our agent: Develop, evaluate, and optimise the skills that make up our agent. Curate datasets, iterate on improvements, test changes, and ship successful approaches into production.

  • Shape our internal AI platform: Contribute to shared libraries, patterns, and standards for how we build, evaluate, and deploy agents across customers. Help define how we approach prompting, tool orchestration, retrieval, and monitoring.

  • Experiment and prototype: Keep up with the latest in NLP, agentic systems, and generative AI. Prototype against our hardest problems with a bias toward shipping experiments quickly rather than long research cycles.

  • Analyse data: Work across customer queries, support tickets, and related data to find patterns and identify what our agents could automate next.

  • Drive technical decisions: Scope your own work, push back when the framing is wrong, and tell us when the plan needs to change.

💡 What you’ll bring

  • 4+ years of professional software engineering experience, with a meaningful focus on Machine Learning, NLP, or applied AI.

  • End-to-end ownership of production systems: you've designed it, shipped it, watched it break, and iterated. You can point to specific moments where you drove a decision forward.

  • Hands-on experience shipping LLM-based features or agent systems into production, not just prototypes. Go experience a plus.

  • Strong Python skills: clean, testable, observable production-grade code.

  • You're always automating. Your default reaction to a repetitive task is to build something for it.

  • Comfort reasoning about trade-offs (accuracy vs latency, coverage vs precision, cost vs quality), framed around what matters to the user and the business.

  • A product-driven posture: you've worked closely with PMs, customers, or domain experts, and translated ambiguity into shipped solutions without needing a perfect spec.

  • A preference for fast iteration over long research cycles.

Why join Gradient Labs?

This is a unique chance to be part of a team working with cutting-edge technology to reshape how businesses will operate in the future. Over the next 10 years, every company will need to embrace AI-powered operations to stay competitive, and this role puts you right in the middle of that transformation.

You’ll tackle challenging and new problems, work with some of the most exciting brands across different industries, and be surrounded by a passionate, smart team that’s driven to build something groundbreaking.

Frequently Asked Questions

Is the salary disclosed for the AI Engineer position at gradient-labs?
The salary for this AI Engineer role at gradient-labs is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Is the AI Engineer job at gradient-labs remote?
Yes, this AI Engineer position at gradient-labs is remote, with team members based in London Office. You can work from home or anywhere in the supported regions.
Is the AI Engineer role at gradient-labs full-time or part-time?
This is listed as a FullTime position. It is posted as a AI Engineer role in the Technology department at gradient-labs.
Which team or department does the AI Engineer at gradient-labs belong to?
This AI Engineer position is part of the Technology department at gradient-labs. See the full job description for more information about the team structure and responsibilities.
How do I apply for the AI Engineer position at gradient-labs?
Click the "Apply Now" button on this page. You will be redirected to gradient-labs's official application portal hosted on ashby where you can submit your application directly.
When was the AI Engineer job at gradient-labs posted?
This AI Engineer position at gradient-labs was posted on Mar 11, 2025. Apply as soon as possible — early applications are often reviewed first.
AI Engineer
gradient-labs
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