Lead Gen AI Engineer [T500-22010]

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 countrys talented workforce and advance their capabilities to serve their clients better.

Lead GenAI Engineer

Reports To Manager of GenAI Engineering

Job Summary:

This is a senior-level role on the Innovation Analytics & AI team, responsible for designing, architecting, and implementing scalable Generative AI applications and infrastructure using leading LLMs (e.g., OpenAI, Gemini, Llama2, GPT-4) and multi-modal models within Azure. This role collaborates with Solution Architects to analyze requirements, lead consensus on implementation, and ensure performance, scalability, and security while aligning with enterprise architecture. The role develops robust data pipelines and Retrieval-Augmented Generation (RAG) workflows using tools like Azure AI Search, ADF Pipelines, LangChain, Semantic Kernel, and Promptflow, while leading prompt engineering, fine-tuning, and model optimization for custom business use cases. This position mentors development staff, influences enterprise initiative prioritization, and drives innovation by integrating cutting-edge technologies. Ensures system reliability, supports production deployments, and fosters cross-functional collaboration to deliver high-impact AI solutions.

Essential Functions & Responsibilities:

Description:

GenAI Application Design & Implementation:

• Design, architect, and implement scalable Generative AI applications and infrastructure using LLMs (e.g., OpenAI, Gemini, Llama2, GPT-4), multi-modal models, and open-source frameworks within Azure.
• Develop robust data integration pipelines and RAG workflows using tools like Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, ADF Pipelines, LangChain, Semantic Kernel, and Promptflow.
• Lead prompt engineering, fine-tuning, and model optimization for custom business use cases, ensuring performance, accuracy, and ethical compliance through rigorous testing (prompt evaluation, bias detection, hallucination analysis, and benchmarking). Advise and implement a roadmap for infrastructure, GenAI model catalogs, and frameworks aligned with business goals.

System Support & Operational Excellence:

• Support AI developers, data analysts, and data scientists in accessing and interacting with Generative AI solutions, resolving issues related to prompt engineering, accuracy, relevancy, and performance through root cause analysis.
• Monitor system performance, storage capacity, and reliability using tools like Azure Application Insights, 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 monitoring and troubleshooting. Deliver clear, professional communication to users, management, and teammates, providing ad hoc data extracts and analysis to meet tactical business needs.

Innovation & Technology Leadership:

• Serve as a role model in continuous improvement by experimenting with emerging technologies and articulating their value to the product organization.
• Collaborate with Solution Architects to deliver enterprise initiatives such as application security, API design, architecture, and test automation, driving innovation through cutting-edge Generative AI strategies.
• Act as a subject matter expert in tools and technologies, lead internal learning forums, set forum objectives, and promote the adoption of new technologies and methods. Demonstrate deep understanding of the technology and business landscape to solve complex business challenges.

Mentorship & Team Leadership:

• Mentor and coach development staff across functions, fostering a culture of learning, excellence, and cross functional collaboration.
• Lead design reviews, influence enterprise initiative prioritization, and guide the team on best practices, test automation strategies, and infrastructure design. Facilitate optimal backlog execution, mentor developers in designing complex business applications, and provide guidance on effective estimation techniques.
• Collaborate with Solution Architects to reduce technical debt and ensure system reliability, performance, and ethical standards in AI systems.

Cross-Functional Collaboration & Technical Excellence:

• Collaborate with Solution Architects to analyze requirements, lead consensus on implementation, and align with enterprise architecture for seamless integration of heterogeneous data.
• Actively participate in peer code reviews, write and integrate automated tests into CI/CD pipelines, and contribute to post-deployment test automation frameworks to improve test efficiency, coverage, and stability.
• Support production deployments with detailed documentation and risk mitigation strategies, ensuring high quality, secure, and maintainable software.

Skills:

• Expertise with GenAI tools (Azure AI Search, Semantic Search, Hybrid Search, Document Intelligence, Skillsets, Generative RAG Search, ADF Pipelines, LangChain, Semantic Kernel, Promptflow) *Proficiency in leading LLMs (OpenAI, Gemini, Llama2, GPT-4) and multi-modal models
• Advanced knowledge of prompt engineering, fine-tuning, and model optimization
• Experience with RAG workflows, agentic AI frameworks, and ethical AI practices (bias detection, hallucination analysis)
• Strong understanding of CI/CD pipelines, automated testing, and test automation frameworks
• Exceptional mentorship, leadership, and communication skills
• Deep knowledge of enterprise architecture, application security, and API design
• Commitment to driving innovation and adopting emerging technologies

Minimum 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): Bachelors Degree, preferably in Computer Science, Data Science, Artificial Intelligence, or equivalent experience

Experience:

• Minimum Years of Experience Required to Perform Essential Job Functions: 5

Additional Experience Qualifier (optional):

• Extensive experience in designing and implementing Generative AI applications, RAG workflows, and data pipelines in production environments.