Job Location: Glasgow (Hybrid - 3 days in the office) Primary Responsibilities and Objectives:

Act as the go‑to expert for Azure AI Search (Azure Cognitive Search), safeguarding best practices in implementation, ingestion, and optimization Partner with the Azure AI Search team to understand the platform's capabilities, roadmaps, and governance Lead the ingestion of documents into Azure AI Search, ensuring proper metadata tagging, data quality, and relevance Set up Retrieval-Augmented Generation (RAG) architecture to deliver accurate responses against a document corpus of approximately 500 documents Optimise and tune Azure AI Search indexes for best performance, relevance, and accuracy Identify and implement key features of Azure AI services needed for successful deployment Work with clients and technical teams to define use cases, document workflows, and solution architecture Contribute to establishing robust MLOps and CI/CD pipelines on Azure to streamline deployment and maintenance Maintain compliance with relevant data governance standards, including GDPR, especially concerning PII data Proactively highlight potential risks, suggest improvements, and demonstrate thought leadership in AI solutions Collaborate with multidisciplinary teams including Java developers, Azure AI Search specialists, and co‑pilot engineers

Experience:

Extensive experience with Azure AI and Machine Learning services, especially Azure Cognitive Search Deep understanding of cloud architecture, deployment, and management on Azure Strong programming skills in Python, API integration, and Java Scripting (nice to have) Proven experience in data engineering tasks, model deployment, and MLOps best practices Experience designing, setting up, and managing RAG architectures and search solutions Ability to operate at a strategic level, identifying critical features and risks in Azure AI implementations Familiarity with GDPR and data governance best practices, especially concerning sensitive information Excellent collaboration, communication, and stakeholder management skills

Key Azure AI and Machine Learning Services:

Azure Cognitive Services Azure Machine Learning Azure Search (Azure Cognitive Search) Azure Data Factory/Databricks (potentially for data engineering tasks) Azure Blob Storage and Data Lake (for document storage and ingestion) Azure Logic Apps and Functions (for automation workflows) MLOps tools within Azure for deployment, monitoring, and management

Diversity Statement Synechron are proud to be an equal opportunity employer. Our Diversity, Equity, and Inclusion (DEI) initiative Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We offer flexible workplace arrangements, mentoring, internal mobility, learning and development programmes to support our global workforce. Empowerment and collaboration are at the core of how we operate. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. #J-18808-Ljbffr