Senior AI Engineer

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.

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.

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.

• 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 client platforms and APIs, monitor quality, latency and cost, and document decisions and trade-offs

• 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

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

• 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

• Strong SQL skills and experience with large analytical datasets
• Familiarity with medallion architectures and integrating AI with data pipelines and APIs

• 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

• 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

• 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
• Experience building offline evaluation or A/B testing tooling for search or recommendation
• Experience building human annotation or rating tools
• Experience with event streaming (for example Kafka) or clickstream and web analytics data

• The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
• The opportunity to form part of an amazing, multicultural community of tech experts.
• A highly competitive compensation package.
• Medical insurance.

Parser is committed to fostering an inclusive workplace and providing equal employment opportunities to all applicants regardless of race, religion, gender, sexual orientation, age, disability, or any other protected characteristic under applicable law.

If you require reasonable accommodations during the recruitment process, please let us know and we will work with you to support your participation.

By applying to this role, you acknowledge that your personal data will be processed in accordance with Parser’s Privacy Notice for recruitment purposes.

Parser may use AI-assisted tools during certain stages of the recruitment process to support operational efficiency. Our recruiting teams use AI to streamline note-taking and scheduling. All hiring decisions are made by people, with human review and oversight

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Originally posted on Himalayas