Senior Applied AI Engineer, Product (London)

Fresha; Greater London; Ibrido; GBP 120.000 - 150.000; Tempo pieno

Descrizione del lavoro

Fresha is seeking a Senior Applied AI Engineer for our London product team. You will join a cross-functional group building AI-powered features that customers interact with directly, including AI reception and related tooling.

The role blends senior backend engineering with applied AI work. You will own end-to-end delivery, design systems around the model, and ensure production quality and scalable performance in a hybrid office setting.

Competenze

• 5+ years building and running backend services in production.
• Shipped a product on top of LLM APIs or agent frameworks your users rely on.
• Written evaluations for non-deterministic systems: test sets, graders, LLM-as-judge.
• Understanding retrieval, tool design and MCP; architecture matters more than prompts.
• Consider correctness, idempotency and system reliability when requests arrive twice or timeouts occur.

Mansioni

• Own AI features end to end: design, build, evaluate, ship and support them in production.
• Build the system around the model: services, tools and integrations to enable real work (availability, bookings, payments).
• Prove it works: create evals, graders and production checks to measure impact and reliability.
• Engineer the context: determine what the model knows and which tools it can call.
• Work in real time: balance latency, cost and quality under tight SLAs.
• Learn from real conversations: analyze transcripts and telemetry to drive next changes.
• Collaborate with Product, Design, Support and other engineers from first talk through release.
• Shape our architecture, AI practices and engineering practices with senior judgment.

Conoscenze

Backend services

LLMs / AI agents

Evaluations

Context & tool design

Distributed systems

Cost & latency

Product sense

AI in workflow

Backend languages

Descrizione del lavoro

Senior Applied AI Engineer, Product (London)

About Fresha

Fresha is the leading AI-powered operating system for the global beauty and wellness industry, giving businesses everything they need to run smarter, grow faster and build stronger client relationships.

In May 2026, Fresha secured an $80M growth investment from KKR at a valuation of $1B, officially reaching unicorn status and bringing total funding raised to $285M. Already profitable, Fresha is using this investment to accelerate global expansion and drive the next generation of AI and product innovation.

Today, Fresha operates at global scale, with offices across Europe, North America, the Middle East and Asia Pacific. Our platform is trusted by 130,000+ beauty and wellness businesses across 120 countries, with more than 1.5 billion appointments booked to date.

Our mission is simple: help beauty and wellness businesses grow by giving them the technology they need to attract clients, manage their operations and run their business in one place.

We’re continuing to scale rapidly across markets, teams and products, making this an exciting time to join us.

Role Overview

Senior Applied AI Engineer | The Bower, 207-211, Old St, Tower, London EC1V 9NR | Four days in office, Wednesdays remote

You’ll join a cross-functional product team and report to its Team Lead. The team builds AI products that Fresha's partners and their clients use directly: today that means an AI receptionist that answers a salon's phone, books appointments and hands off to a human when it should, and the support tooling around it.

This is a hybrid role: half senior backend engineer, half applied AI engineer. The AI is only as good as the system around it. A model that gives a great answer is no use if the booking it promises doesn't exist, the call drops when a downstream service is slow, or nobody can tell whether last week's prompt change made things better or worse. You’ll own both halves.

We work on a short feedback loop. Your change usually reaches production the same day you write it, behind a feature flag. The team that builds a service looks after it, including a shared on‑call rota. Everyone on the team works across the whole stack; there's no “AI person” and “backend person”.

Every engineer gets Claude, Codex or Cursor from day one, and people build their own agent workflows rather than being handed one. We look for engineers who know how to break work up, how to review what comes back, and how to stand behind the result.

What You’ll Do

• Own AI features end to end: Design it, build it, evaluate it, ship it, and look after it once real customers are talking to it.

• Build the system around the model: The services, tools and integrations an agent needs to do real work: checking availability, making bookings, taking payments, escalating to a human. Correct when it retries, safe when it's wrong.

• Prove it works: Build the evals, graders and production checks that tell us whether a change made the product better. Treat them as part of the product, with their own accuracy you measure and improve.

• Engineer the context: Decide what the model knows, what tools it has and how they're described. Most quality gains come from here, not from the prompt.

• Work in real time: Voice and chat run on tight latency budgets. You’ll balance model choice, cost, latency and quality, and keep all four in view.

• Learn from real conversations: Read transcripts, instrument runs end to end (traces, cost, latency, outcomes), and turn what you find into the next change.

• Work with the rest of the team: Product, Design, Support and other engineering teams, from the first conversation through to release.

• Have a say in how we build: Our architecture, our AI practices and our engineering practices aren’t fixed. We expect senior engineers to push on all three.

Our stack: Elixir and TypeScript services, Postgres, Kafka for events, gRPC or GraphQL for synchronous calls, all running in Kubernetes. Our AI products are built on LLM APIs and agent frameworks such as LangGraph, with Twilio for telephony and ElevenLabs for speech, and connect to the rest of Fresha's platform through MCP and our own service APIs. Fresha's wider platform is Ruby, Elixir and TypeScript, so you’ll read a lot of code you didn’t write.

What We're Looking For

• Experience: 5+ years building and running backend services in production.

• Built with LLMs, not just used them: You’ve shipped a product on top of LLM APIs or an agent framework that real users depend on, and you’ve had to make it reliable. You know where models fail and how to design around it.

• Evals: You’ve written evaluations for non-deterministic systems: test sets, graders, LLM-as-judge, and you know when to trust each. You’d rather measure than guess.

• Context and tool design: You understand that what an agent knows and what tools it can call matter more than the prompt. Retrieval, tool design and MCP are familiar territory.

• Correctness: You think about what happens when a request arrives twice, a downstream call times out halfway through, or an agent takes an action it shouldn’t. You design for it rather than finding out later.

• Distributed systems: You’ve built and run services at scale, and you know how they fail. Event-driven design with Kafka or equivalent is a plus.

• Cost and latency: You know that the right model for a task depends on the task, and you keep spend and response time in view.

• Product sense: You care whether customers get what they need, not just whether the code is clean. You’re happy reading transcripts and talking to the people who use what you build.

• AI in your workflow: You use AI coding tools day to day and have a clear view of where they help and where they don’t. You’ve built your own workflows, and you review what comes back before it ships.

• Languages: Strong in at least one backend language. We don’t expect Elixir on day one, but we do expect you to pick things up fast.

• Pragmatic: You’d rather use what exists than build something new, and you can tell the difference between a demo and a product people rely on.

At Fresha, we value passion and potential as much as specific skills. If you’re enthusiastic and eager to learn, we encourage you to apply, even if you don’t meet every listed requirement.

Your Opportunity at Fresha

• AI that customers actually use: Your work talks to real people every day, at the front desk of thousands of businesses. You’ll know quickly whether it helps.

• Scale: Around 1 million bookings a day across 120 countries, and the payments that go with them. The actions our AI takes have real consequences.

• Speed: We release daily, 500+ deploys a day, with not much standing between your branch and your users.

• Ownership: A small team with the tooling, data and permissions to run what it builds, and a say in where the product goes next.

Interview Process

• Screen Stage - Video call with a member of the Talent Team (30min)

• 1st Stage - Technical video/in-person interview (90min)

• 2nd Stage - Practical session: build and evaluate a small AI feature, plus system design (up to 2 hrs)

• Final Stage - Video interview with Head of Engineering / VP of Engineering (60min)

No take-home exercise. We aim to finish the whole process and give feedback within 4 weeks.

Inclusive workforce

At Fresha, we are creating a culture where individuals of all backgrounds feel comfortable.

We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.

We do not discriminate based on race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.

If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.