Lead AI Engineer/Technical Lead

As part of the application process, a candidate account is required to log in and view application(s). Please be sure to check email regularly for information regarding our employment process. Profile Summary: We are seeking a highly motivated and experienced Technical Lead to join our dynamic AI and ProductLIFE CoE. This role is ideal for professionals with 6+ years of post-university experience who have demonstrated the ability to apply emerging technologies effectively and operationalize them in AI-driven environment. Experience with graph technologies and large language models (LLMs) is encouraged. Profile Responsibilities: Lead the design, development, and deployment of AI solutions, ensuring scalability and robustness. Mentor and guide a team of data scientists and engineers, fostering a culture of continuous learning and innovation. Collaborate with cross-functional teams, including actuaries, product managers, and cloud engineers, to integrate AI tools into existing workflows and systems. Drive the exploration and implementation of graph-based algorithms and LLMs to solve complex business problems. Ensure best practices in MLOps are followed for efficient model deployment and monitoring. Stay current on emerging tools in the GenAI and machine learning ecosystem (e.g., LangChain, Hugging Face, vector databases, etc.). Explore and evaluate emerging technologies (e.g., neuromorphic computing, edge AI, quantum ML) that have the potential to transform the industry over the next 3–5 years. Drive our mission to lead the technology pillar of RLUS strategy to become a data-driven, AI-enabled company obsessed with improving customer outcomes Technical & Functional Skills: Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Math, Statistics, or related fields. 6+ years of experience in data science or AI roles, with at least 2 years in a leadership position. Demonstrated experience in deploying AI solutions into production environments. Familiarity with MLOps practices and deploying models to production environments. Proficiency in Python, including libraries such as pandas, scikit-learn, numpy, and matplotlib. Strong understanding of graph databases (e.g., Neo4j) and graph algorithms. Experience with large language models and natural language processing techniques. Familiarity with Jupyter notebooks, Git, and APIs. Strong communication skills and ability to work collaboratively in a hybrid or remote team environment. Experience working in startup environments, demonstrating adaptability and a proactive approach to problem-solving and comfort with ambiguity in fast-paced innovation settings. Exposure to tools such as LangChain, Pinecone, Weaviate, or other vector databases. Hands-on experience with cloud platforms (e.g., AWS, Azure, or GCP). Familiarity with MLOps practices and deploying models to production environments. Proficiency in Japanese is preferred, though not a requirement. Life & Annuity insurance and/or Financial Services experience is a Plus but not required Experience Required: Minimum of 6 years in technology, with 3–5 years in hands-on AI and Data Science roles involving technical leadership, team mentorship, and delivery of high-impact solutions. Critical Skills At Resolution Life , we have identified the following critical skills which are key to success in our culture: Customer Focused: Passionate drive to delight our customers and offer unique solutions that deliver on their expectations. Critical Thinking: Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution. Team Mentality: Partnering effectively to drive our culture and execute on our common goals. Business Acumen: Appreciation and understanding of the financial services industry in order to make sound business decisions. Learning Agility: Openness to new ways of thinking and acquiring new skills to retain a competitive advantage. Originally posted on Himalayas