Senior AI Engineer

Senior Backend Engineer (Python)
Who is Parser?
Technology alone does not create impact - the right teams do. Founded in 2018, Parser is a boutique technology services and consulting firm helping global organisations solve complex business challenges through digital transformation, product development and AI enablement.
We are a fast-growing team of 340+ engineers and consultants across Europe (UK, Spain, Portugal), the Americas (US, Argentina, Uruguay, Colombia), and the Middle East. We combine global reach with a mindset focused on agility, senior expertise, and close collaboration.We work as an extension of our clients’ teams, helping them define the right problems, shape solutions, and deliver technology-driven outcomes that create measurable business value. Our expertise spans software engineering, AI & data, product development, and customer experience, delivered by teams that combine strong technical depth with a consulting mindset.
Why Join Us?
If you are looking for a place where you can think beyond execution, take true ownership of outcomes, influence decisions, and continuously learn alongside top-tier specialists in a truly global environment, we’d love to meet you.
How will you impact?
Parser is looking for an experienced AI and Backend Engineer to join a client delivery team working on Search with one of the largest multinational retail companies, primarily known as a supermarket chain.
You will help build AI-enabled tools that help Search teams find problems, test changes and measure relevance more quickly, all built on a shared data foundation. The role combines strong Python backend engineering with hands-on Generative AI experience, and you should be comfortable moving from a working prototype on real data to a production release.
You will make practical decisions about quality, cost, latency and risk, and recognise when deterministic rules, statistical thresholds or traditional machine learning are a better answer than an LLM. We are looking for someone who works collaboratively, shares progress early and focuses on solving real user problems rather than applying technology for its own sake.
Your key responsibilities:
Design and build AI-enabled features that turn search behaviour, diagnostics and quality data into prioritised, actionable insights, using LLMs where they add value
Build backend services and APIs for tools that collect and combine human relevance judgements
Turn the existing offline evaluation tool into on-demand environments that developers can run in the CI/CD pipeline
Define and automate checks on the accuracy and reliability of AI features, including LLM-based relevance judgements
Work with product, design, data science and Search colleagues to turn prototypes into production releases
Integrate with existing Tesco platforms and APIs, monitor quality, latency and cost, and document decisions and trade-offs
How you'll work
Share work early through documentation, demonstrations and incremental pull requests
Own deliverables within agreed architecture and engineering practices, and communicate decisions, risks and trade-offs clearly
Work closely with Search and data science colleagues to assess the quality of AI-generated outputs
Experiment quickly, test assumptions against real data and iterate using evidence
Balance exploration with delivery, and avoid unnecessary complexity early on
Design for trust, clarity and adoption by the people who use the tools
Recognise when deterministic rules, traditional machine learning or human review are more appropriate than an LLM
What you'll bring to the role:
Generative AI and applied machine learning
Hands-on experience building LLM applications in production, including prompt design, structured outputs and API integration
Understanding of embeddings, semantic search and hybrid retrieval, and their trade-offs against lexical search
Ability to compare models and approaches on quality, latency, security and cost
Evaluation and reliability
Experience building offline evaluations and benchmarks with labelled datasets, and using LLMs as judges calibrated against human labels
Understanding of ranking metrics such as nDCG, Precision at K and MRR, and of inter-rater agreement
Awareness of hallucination, bias, drift and privacy risks, and experience designing human review
Data and platform engineering
Strong SQL skills and experience with large analytical datasets
Familiarity with medallion architectures and integrating AI with data pipelines and APIs
Software engineering
Strong Python skills, including maintainable backend services and APIs
Good testing discipline across application, data and AI components
Experience with CI/CD, containerisation and cloud infrastructure, ideally Microsoft Azure
Qualifications
Five or more years of professional experience across software engineering, data engineering, machine learning or applied AI
Demonstrated experience delivering AI-enabled systems beyond isolated proofs of concept
Proven ability to ship iterative, user-focused solutions with appropriate attention to reliability and safety
Strong written and verbal communication skills, including explaining technical choices and evaluation results to non-technical stakeholders
A collaborative approach to multidisciplinary product delivery
Nice to have
Experience in retail or ecommerce search, including product taxonomy and long-tail queries
Hands-on experience with Elasticsearch or another production search platform, or with a vector database

Employment type
Full-Time

Work arrangement
Yes