Data Engineer (AI / ML)
Role details
Job location
Tech stack
Job description
We are investing massively in developing next-generation AI tools for multimodal datasets and a wide range of applications. We are building large scale, enterprise grade solutions and serving these innovations to our clients and WPP agency partners. As a member of our team, you will work alongside world-class talent in an environment that not only fosters innovation but also personal growth. You will be at the forefront of AI, leveraging multimodal datasets to build groundbreaking solutions over a multi-year roadmap. Your contributions will directly shape cutting-edge AI products and services that make a tangible impact for FTSE 100 clients., * Collaborate closely with data scientists, architects, and other stakeholders to understand and break down business requirements.
- Collaborate on schema design, data contracts, and architecture decisions, ensuring alignment with AI/ML needs.
- Provide data engineering support for AI model development and deployment, ensuring data scientists have access to the data they need in the format they need it.
- Leverage cloud-native tools (GCP/AWS/Azure) for orchestrating data pipelines, AI inference workloads, and scalable data services.
- Develop and maintain APIs for data services and serving model predictions.
- Support the development, evaluation and productionisation of agentic systems with:
- LLM-powered features and prompt engineering
- Retrieval-Augmented Generation (RAG) pipelines
- Multimodal vector embeddings and vector stores
- Agent development frameworks: ADK, LangGraph, Autogen
- Model Context Protocol (MCP) for integrating agents with tools, data and AI services
- Google's Agent2Agent (A2A) protocol for communication and collaboration between different AI agents
- Implement and optimize data transformations and ETL/ELT processes, using appropriate data engineering tools.
- Work with a variety of databases and data warehousing solutions to store and retrieve data efficiently.
- Implement monitoring, troubleshooting, and maintenance procedures for data pipelines to ensure the high quality of data and optimize performance.
- Participate in the creation and ongoing maintenance of documentation, including data flow diagrams, architecture diagrams, data dictionaries, data catalogues, and process documentation.
Requirements
Do you have experience in Spark?, Do you have a Master's degree?, * High proficiency in Python and SQL.
- Strong knowledge of data structures, data modelling, and database operation.
- Proven hands-on experience building and deploying data solutions on a major cloud platform (AWS, GCP, or Azure)
- Familiarity with containerization technologies such as Docker and Kubernetes.
- Familiarity with Retrieval-Augmented Generation (RAG) applications and modern AI/LLM frameworks (e.g., LangChain, Haystack, Google GenAI, etc.).
- Demonstrable experience designing, implementing, and optimizing robust data pipelines for performance, reliability, and cost-effectiveness in a cloud-native environment.
- Experience in supporting data science workloads and working with both structured and unstructured data.
- Experience working with both relational (e.g., PostgreSQL, MySQL) and NoSQL databases.
- Experience with a big data processing framework (e.g., Spark)., * API Development: Experience building and deploying scalable and secure API services using a framework like FastAPI, Flask, or similar.
- Experience partnering with data scientists to automate pipelines for model training, evaluation, and inference, contributing to a robust MLOps cycle.
- Hands-on experience designing, building, evaluating, and productionizing RAG systems and agentic AI workflows.
- Hands-on experience with vector databases (e.g., Pinecone, Weaviate, ChromaDB).
Benefits & conditions
Pulled from the full job description
- Company pension
- Paid volunteer time
- Private medical insurance
- Flexible schedule, * Benefits - enhanced pension, life assurance, income protection, private healthcare;
- Remote working - café, bedroom, beach - wherever works;
- Truly flexible working hours - school pick up, volunteering, gym;
- Generous Leave - 27 days holiday plus bank holidays and enhanced family leave;
- Annual bonus - when Satalia does well, we all do well;
- Impactful projects - focus on bringing meaningful social and environmental change;
- People oriented culture - wellbeing is a priority, as is being a nice person;
- Transparent and open culture - you will be heard;
- Development - focus on bringing the best out of each other;
Satalia is home to some of the brightest minds in AI and if you're looking to join a company who not only values autonomy and freedom, but embraces a culture of inclusion and warmth, we'd love to hear from you.