Lead Data and AI Solution Engineer

The Lead Data & AI Solution Engineer is responsible for architecting and delivering innovative data and AI solutions that drive business transformation and operational excellence. This role is critical in enabling advanced analytics and AI-driven capabilities to support strategic objectives within the insurance domain.

• Architect end-to-end GenAI solutions for insurance use cases, incorporating semantic search, vector databases, embedding models, and RAG-enabled data architectures to deliver intelligent, context-aware AI capabilities across structured and unstructured data sources.
• Design and implement knowledge bases, vector databases, and embedding pipelines to enable efficient retrieval-augmented generation (RAG) and contextual AI workflows, ensuring compliance with enterprise data architecture and governance standards.
• Benchmark and evaluate Large Language Models (LLMs) for targeted business applications to ensure performance, relevance, and scalability.
• Hands-on experience with post-training and fine-tuning LLMs and embedding models for domain-specific optimization.
• Knowledge of LLM inference frameworks such as vLLM and Hugging Face for efficient model deployment and serving.
• Drive continuous improvement of AI agents through optimization, rigorous testing, and solution design reviews.
• Familiarity with agentic AI systems and their application in enterprise workflows for autonomous task execution and orchestration.
• Familiarity with Natural Language Processing (NLP) use cases, such as sentiment analysis and article summarization, to support diverse business needs.
• Ensure smooth production deployment in collaboration with stakeholders, maintaining compliance with data governance and security policies.
• Collaborate cross-functional collaboration to deliver secure, high-quality, and compliant AI-driven solutions.
• Strong proficiency in AWS and cloud-based solution architecture.
• Excellent problem-solving and interpersonal skills, with the ability to perform under pressure.
• Meticulous, detail-oriented, and committed to delivering results within tight deadlines.
• Adaptable and dependable, with flexibility to support during peak periods.
• Effective communicator and strong team player.

• Master’s degree above in Data Science, Statistics, Computer Science, Computer Engineering, Economics, Actuarial Science or equivalent disciplines with extensive use of data for analysis
• Proven expertise in machine learning and familiarity with Large Language Models.
• Practical knowledge on machine learning techniques and advanced statistical techniques and concepts
• Solid and hands-on engineering and coding skills such as Python, Pyspark, Scala, SQL, and R with experience in relational databases and Hadoop infrastructure.
• Proficient in integration and orchestration of AI/ML tools and library
• Exposure to micro services and architecture
• In-depth understanding of model life cycle management
• Good written and verbal communication skills with demonstrating the ability to communicate the business benefits provided by analytics insights
• Experience in big data frameworks like Hive, Spark and Hadoop
• Experience in using data visualization software such as Tableau/Qlik/PowerBI
• Experience in using AWS/GCP will be preferred
• Experience in Insurance or Financial Services is a plus
• Willing to learn and positive, can-do attitude