Position: GenAI Data Engineer Location: London or Edinburgh (Hybrid-2 days a week from office) 6 months contract position Your responsibilities: \* Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high‑volume data processing. \* Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost‑efficient ingestion, transformation, and storage. \* Develop, finetune, benchmark, and evaluate GenAI/LLM models, including custom training and inference optimization. \* Implement and maintain RAG pipelines, vector databases, and document-processing workflows for enterprise GenAI applications. \* Build reusable frameworks for prompt management, evaluation, and GenAI operations. \* Collaborate with cross-functional teams to integrate GenAI capabilities into production systems and ensure high-quality data, governance, and operational reliability Your Profile Essential skills/knowledge/experience: \* Strong experience with PySpark, distributed data processing, and largescale ETL/ELT pipelines. \* Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing CDC, SCD Type 1/2/3 patterns for reliable data warehousing. \* Advanced proficiency in Python for data engineering, automation, and ML/GenAI integration. \* Hands on expertise with AWS services (S3, Glue, Lambda, EMR, Bedrock / custom model hosting). \* Practical experience with Gen AI/LLM model creation, finetuning, benchmarking, and evaluation. \* Solid understanding of RAG architectures, embeddings, vector stores, and LLM evaluation methods. \* Experience working with structured and unstructured datasets (documents, logs, text, images). \* Familiarity with scalable data storage solutions (Delta Lake, Parquet, Redshift, DynamoDB). \* Understanding model optimization techniques (quantization, distillation, inference optimization). \* Strong capability to debug, tune, and optimize distributed systems and AI pipelines. \* Desirable skills/knowledge/experience: (As applicable) \* Pyspark, Python, SQL, AWS, Gen AI