Job Title

About FM:FM is a 190-year-old, Fortune 500 commercial property insurance company of 6,000+ employees with a unique focus on science and risk engineering. Serving over a quarter of the Fortune 500 and major corporations globally, they deliver data-driven strategies that enhance resilience, ensure business continuity, and empower organizations to thrive. FM India located in Bengaluru is a strategic location for driving FM's global operational efficiency that allows them to leverage the country’s talented workforce and advance their capabilities to serve their clients better.Senior GenAI EngineerReports To Manager of GenAI EngineeringJob Summary:This is a mid-level role on the Data Analytics team, responsible for leading the development of high-quality, secure, and maintainable generative AI solutions and business applications. This role collaborates with Solution Architects to analyze requirements, design AI-enabled applications, and ensure usability, extensibility, and performance while aligning with enterprise architecture and data integration standards. The role designs and implements robust data pipelines and Retrieval-Augmented Generation (RAG) workflows using tools like Prompt flow, Azure AI Search, ADF Pipelines, and Vector DBs, ensuring reliable flow of heterogeneous data into LLM-powered systems. This position leads design reviews, mentors junior team members, and drives continuous improvement by integrating emerging technologies. Supports production deployments, monitors system performance with tools like Azure Application Insights and Dynatrace, and fosters a collaborative team environment focused on innovation and excellence.Essential Functions & Responsibilities:Description:GenAI Development & Pipeline Implementation:Lead the development of secure, maintainable, and high-quality generative AI solutions, designing robust software engineering code and data pipelines for heterogeneous data using tools like Prompt flow, Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, ADF, Azure Functions, Vector DBs, Azure OAI, AI Hub, Agents, and Assistants. Develop and maintain generative AI components, including prompt engineering, model integration, and inference pipelines, ensuring reliable flow of data into LLM-powered systems. Implement and optimize Retrieval-Augmented Generation (RAG) workflows, integrating them into CI/CD pipelines to ensure code quality and system reliability. Develop observability metrics using Azure Application Insights and Dynatrace for real-time system monitoring and performance insights.System Support & Operational Excellence:Support developers, data analysts, and data scientists in accessing and interacting with generative AI solutions, resolving issues related to prompt engineering, accuracy, relevancy, and performance. Monitor system performance, storage capacity, and reliability, identifying opportunities for optimization and addressing production issues promptly with proper validation and deployment steps. Support the development and maintenance of RAG pipelines and LLM-based solutions, ensuring high availability and performance through proactive troubleshooting. Consult with team members on infrastructure configuration and maintenance, delivering clear and professional communication to users, management, and teammates.Innovation & Continuous Improvement Stay current with emerging technologies and industry trends in generative AI, integrating cutting-edge strategies to solve complex business problems. Collaborate with Solution Architects to align AI initiatives with enterprise goals, contributing to key initiatives such as application security, architecture, and test automation. Lead and contribute to internal learning forums, sharing cross-functional knowledge and promoting the adoption of new technologies and methods. Demonstrate broad technical expertise and domain knowledge to enable leadership across diverse product teams.Mentorship & Team Leadership:Act as a technical mentor to junior team members, coaching them to align with best practices and fostering a culture of learning and excellence. Encourage active team contributions during design and implementation phases, serving as a role model in delivery accountability, process discipline, and a growth-oriented mindset. Proactively identify and communicate impediments, organize work tasks in the team backlog based on prioritization, and escalate conflicting priorities to ensure team success. Provide reliable production support (occasional nights/weekends) and foster a collaborative environment with strong communication and meaningful feedback.Cross-Functional Collaboration & Design Leadership:Collaborate with Solution Architects, product owners, data scientists, and engineers to analyze requirements and design AI-enabled applications that meet enterprise standards. Lead and participate in design reviews, contribute to product backlogs, and support cross-functional collaboration for successful implementation. Apply design patterns to build secure, maintainable, and testable software, ensuring performance, accuracy, and ethical standards through rigorous validation and monitoring.Skills:Proficiency with GenAI tools (Promptflow, Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, ADF, Azure Functions, Vector DBs, Azure OAI, AI Hub, Agents, Assistants)Expertise in data integration pipelines (Azure Search, ADF Pipelines) and RAG workflowsKnowledge of system monitoring tools (Azure Application Insights, Dynatrace)Experience with CI/CD pipelines, automated testing, and peer code reviewsUnderstanding of prompt engineering, model integration, and inference pipelinesStrong collaboration, mentorship, and leadership skillsCommitment to staying current with emerging trends in generative AI and LLMsMinimum Qualifications:Except where required by licensure or regulation a combination of comparable education and experience may be used to satisfy qualification requirements.Education:Minimum Education Required to Perform Essential Job Functions: 4 Year / bachelor's degree Specific Degree, if required (ex - Engineering, Juris Doctorate, etc): Bachelor’s Degree, preferably in Computer Science, Data Science, Artificial Intelligence, or equivalent experienceExperience:Minimum Years of Experience Required to Perform Essential Job Functions: 2Additional Experience Qualifier (optional): Experience with generative AI solutions, data pipelines, and RAG workflows in production environments.