Role Overview: You will be responsible for designing, building, and iterating generative AI solutions, specifically focusing on retrieval augmented generation (RAG) pipelines, embedding, retrieval, prompt orchestration components, document processing, information extraction, summarisation, and content generation use cases. Additionally, you will support evaluation frameworks for GenAI solutions, contribute to creating reusable AI and data components, collaborate with onshore AI leads, data engineers, and delivery management, and adhere to governance, security, and architectural standards. Key Responsibilities: - Design, build, and iterate generative AI solutions, including RAG pipelines, embedding, retrieval, and prompt orchestration components, and document processing. - Support evaluation frameworks for GenAI solutions by managing validation datasets, quality scoring, and human in the loop review processes. - Contribute to the creation of reusable AI and data components across different use cases, focusing on standardised ingestion, retrieval, and evaluation approaches. - Work as part of a prioritised backlog, delivering incremental thin slices of functionality to meet project requirements. - Collaborate closely with onshore AI leads, data engineers, and delivery management to ensure project success. - Support documentation, walkthroughs, and knowledge transfer to client teams to facilitate understanding and adoption of AI solutions. Qualification Required: - 7 to 8 years of experience as a Data Scientist and/or AI Engineer. - Hands-on experience with Databricks. - Proven experience in building Generative AI solutions, such as LLM-based applications, RAG pipelines, information extraction pipelines, and prompt engineering. - Solid Python skills for data processing and AI development. - Experience in working with both structured and unstructured data. - Familiarity with evaluation, monitoring, and iterative improvement of ML/AI solutions. - Experience working in distributed delivery teams. - Strong communication skills. Additional Details: Please note that this job posting has been aggregated from an external source, and role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. Role Overview: You will be responsible for designing, building, and iterating generative AI solutions, specifically focusing on retrieval augmented generation (RAG) pipelines, embedding, retrieval, prompt orchestration components, document processing, information extraction, summarisation, and content generation use cases. Additionally, you will support evaluation frameworks for GenAI solutions, contribute to creating reusable AI and data components, collaborate with onshore AI leads, data engineers, and delivery management, and adhere to governance, security, and architectural standards. Key Responsibilities: - Design, build, and iterate generative AI solutions, including RAG pipelines, embedding, retrieval, and prompt orchestration components, and document processing. - Support evaluation frameworks for GenAI solutions by managing validation datasets, quality scoring, and human in the loop review processes. - Contribute to the creation of reusable AI and data components across different use cases, focusing on standardised ingestion, retrieval, and evaluation approaches. - Work as part of a prioritised backlog, delivering incremental thin slices of functionality to meet project requirements. - Collaborate closely with onshore AI leads, data engineers, and delivery management to ensure project success. - Support documentation, walkthroughs, and knowledge transfer to client teams to facilitate understanding and adoption of AI solutions. Qualification Required: - 7 to 8 years of experience as a Data Scientist and/or AI Engineer. - Hands-on experience with Databricks. - Proven experience in building Generative AI solutions, such as LLM-based applications, RAG pipelines, information extraction pipelines, and prompt engineering. - Solid Python skills for data processing and AI development. - Experience in working with both structured and unstructured data. - Familiarity with evaluation, monitoring, and iterative improvement of ML/AI solutions. - Experience working in distributed delivery teams. - Strong communication skills. Additional Details: Please note that this job posting has been aggregated from an external source, and role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.