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ashby

Senior Generative AI Engineer

motorway
Remote, GBR
Full-time
Remote
Discovered 1 weeks ago
generative AIPythonSQLLLM APIsretrieval systemsvector stores
Free

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generative AIPythonSQL
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About Motorway

Motorway is a UK online car-selling platform connecting private sellers with more than 8,000 dealers.

The company was founded in 2017 and uses a technology-led marketplace approach.

Team and role

GenAI Engineering sits within Motorway's Data and AI function alongside Machine Learning and the Machine Learning Data Platform.

The role builds AI applications and agentic workflows from rapid prototype through production-grade systems that deliver measurable value.

The engineer owns prompting, retrieval, agent design, evaluations, guardrails, monitoring, and production operation.

Responsibilities

  • Own AI features end to end, from ambiguous problem definition through reliable, observable production systems.
  • Build retrieval and data foundations and treat retrieval quality as a core engineering problem.
  • Design evaluation and monitoring approaches for quality, reliability, and safety.
  • Build AI applications and agents using LLMs, orchestration, APIs, and data systems.
  • Make decisions about models, cost, and latency and document the reasoning.
  • Prototype quickly and turn reusable patterns into components for team adoption.
  • Raise team quality through code review, design feedback, and standards.
  • Represent technical decisions to product managers and stakeholders.

Required experience and skills

  • Experience shipping AI or ML systems used by real users and staying close to their production behavior.
  • Strong Python skills and practical SQL experience.
  • Experience with testing, error handling, CI/CD, observability, and MLOps practices.
  • Hands-on experience with LLM APIs, retrieval, vector stores, agents with tool use, and structured outputs.
  • Experience with cloud infrastructure; Motorway uses AWS and GCP.
  • Ability to evaluate systems and reason about hallucination, prompt injection, and model failure modes.
  • Ability to choose an appropriate model or a simpler solution for each problem.
  • Ability to provide constructive technical reviews.

Ways of working

  • Curiosity about how systems work and willingness to investigate beyond the first plausible answer.
  • Comfort with ambiguous problems and approaches that are not yet obvious.
  • Honesty about knowledge limits and willingness to involve others early.
  • Ownership of shipped systems, including monitoring behavior and fixing failures.
  • Appreciation for the operational work that makes AI features reliable.
  • Ability to disagree constructively and commit once a decision is made.

Working arrangement

  • The role includes flexible working with two days per week in the London office.

Benefits

  • The package includes a competitive salary, equity scheme, 25 days of holiday, private medical insurance, life assurance, and a pension with a 5% company contribution.
  • Additional benefits include enhanced family leave, a 24/7 employee assistance programme, EV leasing, cycle to work, nursery salary sacrifice, and one paid volunteering day per year.

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