Generative AI Engineer (Product Intelligence)

Brak informacji o wynagrodzeniu

NieokreśloneHybryda·KrakówFull-time

#471106·Dodano 6 dni temu·2

Źródło: Tesco Technology

Aplikuj teraz

Tech Stack / Keywords

Python LLMsAzure OpenAI GPT-4Apache Kafka PostgreSQLpgvectorLangfuseAzure Kubernetes Terraform

Podsumowanie oferty

You will build and take generative AI capabilities into production for the Product Intelligence Platform, which automates product categorisation, enrichment and matching. The role focuses on Python services and pipelines close to the models, including prompt engineering, LLM orchestration, embeddings, scoring and evaluation.

Wymagania

Mandatory skills:

Solid, recent experience building production backend services in Python with a modern framework such as FastAPI, Django or Flask.
Hands-on experience with LLMs and prompt engineering in a production or near-production setting.
Experience with embeddings and vector similarity, using pgvector or an equivalent vector database.
Good understanding of event-driven architectures and Apache Kafka.
Comfort running feasibility studies or proofs of concept and carrying them through to a shipped solution.
Experience with cloud platforms, preferably Azure.
Understanding of software engineering best practices, including CI/CD, testing and code review.
Strong stakeholder communication skills and ability to translate ambiguity into clear requirements and implementation plans.

Nice to have:

Experience with LLM observability and evaluation tooling such as Langfuse.
Experience working with multi-agent systems.
Familiarity with Java/Spring Boot.
Experience with Kubernetes (Azure Kubernetes Service) for container orchestration.
Experience with Infrastructure as Code (Terraform).
Knowledge of the retail or e-commerce domain.
Understanding of data quality and governance principles.
Experience mentoring or upskilling others in applied generative AI, or involvement in hiring.

Obowiązki

Lead generative AI feasibility studies and proofs of concept for product intelligence capabilities, and turn promising results into production designs.
Design and build generative AI solutions that integrate large language models (Azure OpenAI GPT-4) through the GenAI Service facade, including prompt design, evaluation and iteration.
Build and maintain embedding-based similarity and scoring pipelines using PostgreSQL with pgvector.
Contribute to LLM observability and evaluation practices, including regression testing and drift detection as prompts and models change, using tools such as Langfuse.
Support Human-in-the-Loop tooling for data stewards to review and validate generative AI output.
Contribute to responsible Gen AI governance activities, including audit support and structured release criteria for prompt and model changes.
Build event-driven services in Python for high-volume data processing on Kafka.
Collaborate with product managers, data stewards and other engineers to translate ambiguous business problems into technical designs.
Share generative AI knowledge with the wider team and contribute to upskilling.
Optionally represent the team's generative AI work externally, such as at conferences or in the tech community.

Tesco Technology

22 aktywne oferty

Zobacz wszystkie oferty

Aplikuj teraz