Senior Lead, AI Test Engineering (Secunderabad)

Talent500 is hiring for one of its clients. Who are we: Core Insurance Platforms (CIP) is Zurich's global capability responsible for building, running, and evolving core insurance technology. We set a unified, scalable operating modelcovering governance, standards, architecture, service delivery, and reuseso our business units can deliver at speed and scale. CIP is the strategic steward of Zurich's Guidewire ecosystem, aligning platform roadmaps to business strategy while driving stability, modernization, reduced supplier dependency, and long term cost efficiency. India delivery center is one of our global delivery and capability hub. We bring together experts in AI, engineering, analysis, quality, and architecture to deliver product & process solutions, application run services, change and transformation initiatives, and centralized platform services across both on prem and Guidewire Cloud environments. Our teams operate from multiple global delivery centers, supporting Zurich's business units worldwide. Senior Lead AI Test Engineering Role description: Our focus is on advancing our AI capabilities to deliver impactful, scalable solutions that address real business challenges. As part of this journey, we are strengthening our AI engineering and delivery capacity with a hands-on expert who can actively contribute to the design, development, and deployment of AI-based solutions. Today, Artificial Intelligence is transforming how we build, operate, and evolve digital solutions. We are looking for a pragmatic, analytical, and delivery-oriented professional who combines strong technical expertise with a problem-solving mindset to bring AI initiatives from concept to production. As an AI SME Expert, your main responsibility will be to support the end-to-end delivery of AI solutions to support and evolve the Test Engineering Services, bringing both execution capacity (hands-on) and expertise (brains) to the team. You will contribute across the full lifecycle, from ideation and design to development, deployment, and continuous improvement. You will collaborate closely with technical and business stakeholders to ensure that AI initiatives meet business requirements, follow best practices, and generate measurable value for the organization. Profile Summary: We are looking for a hands-on AI expert with 10 to 12 years of experience, who combines strong technical capabilities with a practical mindset and a passion for delivering real business value. The ideal candidate thrives in energetic environments, enjoys solving complex problems, and is comfortable working across both technical and business domains. Responsibilities: Be the Go-To AI expert: - Provide hands-on expertise in designing and implementing AI/ML solutions aligned with business needs and strategic goals. Design & develop AI solutions: - Actively contribute to solution architecture, model development, integration, and deployment of AI capabilities into existing systems. Drive End-to-End delivery: - Support the full lifecycle of AI initiatives, from scoping and prototyping to production deployment and maintenance. Ensure technical excellence: Apply best practices in software engineering, data engineering, and AI development to ensure scalable, secure, and robust solutions. Leverage cloud & data platforms: - Work with cloud-based environments and data pipelines to enable efficient AI solution development and operation. Integrate AI into business processes: - Translate business requirements into AI-driven use cases and ensure seamless integration into operational workflows. Collaborate for success: - Work closely with cross-functional teams (automation, performance and security) to deliver high-value solutions. Promote continuous improvement: - Identify opportunities to optimize performance, reduce manual effort, and enhance solution efficiency through AI capabilities. Ensure robust AI solution delivery: - Build, deploy, and maintain AI/ML models and supporting systems in production environments - Continuously improve solution performance, scalability, and reliability - Apply monitoring, observability, and feedback mechanisms to AI systems - Identify patterns and optimization opportunities using AI-driven insights Bridge technical & business needs: - Translate business problems into technical AI solutions and communicate outcomes effectively to stakeholders. Adopt & apply standards: - Ensure compliance with IT standards, security policies, and governance frameworks in AI development. Monitor value & impact: - Track performance, adoption, and ROI of AI solutions to support decision-making and continuous improvement. Technical Skills: - Machine Learning & Deep Learning: Supervised/unsupervised learning, model evaluation, feature engineering - Generative AI & LLMs: Prompt engineering, fine-tuning, RAG architectures, embeddings - Data engineering fundamentals: Data pipelines, ETL/ELT, data quality, structured & Talent500 i