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      Senior Applied AI Engineer Interview

      23 Feb 2026
      Anonymous interview candidate
      No offer
      Negative experience
      Easy interview

      Application

      I applied through a recruiter. I interviewed at Tomoro AI in Dec 2025

      Interview

      Initial 45m talk with a senior engineer followed by a take home exercise. I would also like to echo a lot of the negative experience comments. The task per se was quite easy: an LLM-based conversational agent over some financial data. As instructed, it should take a few hours, solution should not be complicated, and also they stated that not all ideas need to be implemented. After all, they instructed to spend 25% of time on writing a report that included solution description, 'Future work' and Error analysis. Putting everything together to have a well structured code, run small scale eval to analyse results, do prompt improvements, re-run eval, and conclude with detailed report easily adds up to a few hours. However, the feedback seemed to imply that far more were expected than either necessary for this problem (LLMs+tools or Agentic style solution), or requested in the description or could be finished in a few hours. The feedback also implied using CoT which was again unnecessary for the complexity of the problem and which I also described in detail in the Future work section, but apparently it was ignored. Other negative aspects: - It is the first time I am asked to use LLMs for home exercise and they don't provide with a temp api_key. - In their orig. instructions email, they mentioned it would be possible that I send them one of my projects as opposed to doing the exercise. However, when I offered to opensource a project of mine that included RAG, LLMs, prompting, they declined. In retrospect it seems clear they want you to work on their problem.

      Interview questions [1]

      Question 1

      Design and implement an LLM-driven prototype that can answer conversational dialogue questions over an academic financial dataset
      Answer question

      Other Senior Applied AI Engineer interview reviews for Tomoro AI

      Senior Applied AI Engineer Interview

      27 Oct 2025
      Anonymous interview candidate
      London, England
      No offer
      Neutral experience
      Average interview

      Application

      I applied through a recruiter. I interviewed at Tomoro AI (London, England) in Aug 2025

      Interview

      Similar to other people, the first interview was with the Talent team, mostly motivational and very pleasant. Next stage was a take home test that allegedly takes 4h. I don't think it's a 4h. Similar to what other people have said it's a really lengthy one. Basically, you are asked to build a Q&A bot (agentic and whatnot) based on the CONVFINQA paper from 2023, but avoid using the same methodology. When you consider pydantic validation, API costs (which are not covered), expected to use OpenAI API, and the rest of a proper agentic solution, it adds up. For £135k offered (max), not bad, but agree that might not select good candidates, rather people with time.

      Interview questions [1]

      Question 1

      We’d like you to demonstrate a LLM driven prototype that can answer conversational dialogue questions on any given financial document. For this task we ask you to use a cleaned version of the ConvFinQA Dataset.
      Answer question
      2

      Senior Applied AI Engineer Interview

      27 May 2025
      Anonymous interview candidate
      No offer
      Negative experience
      Average interview

      Application

      I applied through a recruiter. I interviewed at Tomoro AI in May 2025

      Interview

      Chat with recruiter, chat with hiring manager, take-home assignment. "We had stronger coding submissions" and no feedback provided. I spent about 4 hours on the assignment using a lot of boilerplate code from my cookiecutter templates. I have some serious doubts that the person that reviewed it understood what they were looking at. I implemented a fastAPI app that allowed ingesting json files into a SQLite DB with the sqlite-vec extension. Supporting full CRUD operations. Ready to be instrumented with OTEL, with alembic to manage migrations, an LLM completions protocol and an embeddings protocol with mock and concrement implementations to be able to mock all interactions with a query param for dev / testing, all based on LiteLLM for a single interface to swap models, automated retries etc. Exception handlers to obfuscate internal errors, logging middleware. CI/CD mock for unit tests, image builds, deployment to k8s (with helm) and automation of notifications and smoke tests. Yes the RAG implementation was very basic but the focus was on MLOps and production focused engineering which is where my strengths lie and I thought we were in alignment with the hiring manager from the initial conversation.

      Interview questions [1]

      Question 1

      Implement a RAG solution based on some open source dataset for a conversational agent.
      Answer question
      4

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