2 of 2 Retrieval-Augmented Generation Jobs in Reading

IT, Big Data, Security & Privacy, Digital, and Business Unit teams to ensure integration, compliance, and delivery readiness Technology Leadership: Evaluate and leverage modern AI/GenAI capabilities including LLMs, RAG pipelines, MLOps, and cloud-native tooling Governance and Compliance: Ensure solutions adhere to enterprise governance, responsible AI principles, data protection regulations, and security best practices Value Realization: Work with business … complex environments Hands-on experience delivering AI/GenAI solutions in networks, telecommunications, or customer experience domains is strongly preferred Deep understanding of architecture patterns for LLMs, NLP, MLOps, RAG, APIs, and real-time data integration Strong background in working with cloud platforms (GCP, AWS, Azure) and big data technologies (e.g., Kafka, Spark, Snowflake, Databricks) Demonstrated ability to work across More ❯

of AI engineers. Represent AI in senior product, engineering, and vendor forums. Generative AI Delivery Lead design, prototyping, and deployment of GenAI use cases (e.g. co-pilots, AI agents, RAG systems). Establish scalable LLMOps practices including model evaluation, governance, and lifecycle automation. Maintain awareness of emerging models and integration strategies. Machine Learning Engineering: Support the ML Engineer in model … Required Qualifications: Proven experience building and deploying GenAI applications in production. Strong hands-on knowledge of LLMs, prompt engineering, and retrieval-augmented generation (RAG). Practical experience with traditional ML, including data pipelines and MLOps workflows. Working knowledge of statistical modelling and experimentation. Proficiency in Python and at least one additional general-purpose language. More ❯