Level

Granola

AI Engineer (Core Harness)

Granola is hiring an AI Engineer (Core Harness) in London, United Kingdom. It pays £100k-£130k a year and Level rates it ; you can apply on Level.

AI in this role

openaianthropic
rag

Hey! We're team Granola 👋  

If you haven't already, you should check out what we're building, and why you should work here.

We are looking for a self-starting engineer, passionate about applying the latest advancements in LLMs to create user-centric products.

The Core Harness team builds the systems that turn models into useful, reliable agents at Granola: the agent loop, tools, memory, context management and execution environment. We own how those pieces work together, so agents can understand a user’s work, take action across their tools and follow through on complex tasks.

As an AI Engineer on the team, you’ll work across model behaviour and the systems that shape it. That might mean deciding what an agent should remember, helping it recover when a tool fails, or redesigning its execution loop to make use of a new model’s capabilities.

Why you might be a good fit

  • You’ve built with models and investigated their failures. You can explain where a system struggled, how you diagnosed the problem and what made it better.

  • You think across the whole agent. You’re interested in how model behaviour, context, memory, tools and execution interact, and can reason about which part needs to change.

  • You have judgment about agent/model behaviour. You notice when an agent is being unhelpful, taking unnecessary steps or acting with too little information. You care about making it feel capable, responsive and trustworthy.

  • You enjoy a field where the answers keep changing. You try new capabilities, develop your own understanding of their strengths and limitations, and revisit earlier decisions when the evidence changes.

  • Love working in a startup environment (you either have experience working in a startup or are really drawn to the zero-to-one phase)

  • Are fascinated by LLMs. You love to play with them, figure out what makes them tick and get them to do what you want. You scour the web and reddit for others doing the same (you probably follow @goodside on twitter)

In this role, you will:

  • Own the development and application of LLM-based features end-to-end

  • Build and maintain evaluation frameworks for prompt iteration and semantic retrieval

  • Optimize embeddings and vector stores for performance and scalability

  • Interact with users to understand their problems and design solutions

  • Stay up-to-date with the latest trends in LLMs and applied AI practices

  • Collaborate with a cross-functional team of engineers, product managers, designers, and other members to create a cutting-edge product

Your background looks something like:

  • Engineering experience at tech and product-driven companies

  • Shipping multi-provider LLM-based solutions to production (using e.g. OpenAI, Anthropic, Google, etc.)

  • Proficiency with LLM infra platforms (prompt management, logging/tracing, evals)

  • Experience designing large-context LLM systems (RAG, knowledge graphs, hybrid search, memory)

  • Building features end-to-end with TypeScript, React.js, and Node.js

What we offer

We are living in the most exciting time for tool builders since Engelbart's demo in 1968. We want to assemble the best crew to build this future together, here in London. Our compensation philosophy is to pay slightly above market on salary and above market on equity.

We do our best work in person, and so our team spends time together five days per week in our new, bright, and spacious office at Old Street. We are happy to offer relocation assistance to candidates who'll be moving to London to join us.

Lastly, we think amazing talent comes from all kinds of life journeys and experiences. If what is written above speaks to you, whether you look like a fit on paper or not, please reach out.

How we rate this

AI Engineer (Core Harness) at Granola rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGOpenAIAnthropic

Also common in AI engineer jobs at this level

Pay

Typical AI engineer job
$183k

Use the typical AI engineer figure as a reference when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. What are the limits of Anthropic that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: RAG, OpenAI, and Anthropic. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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