Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Develops secure and high-quality production code, and reviews and debugs code written by others. Drives decisions that influence the product design, application functionality, and technical operations and processes. Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle. Influences peers and project decision-makers to consider the use and application of leading-edge technologies. Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture. Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions. Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies. Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics. Promote software and model quality, integrity, and security across the organization Required qualifications, capabilities, and skills. BS in Computer science or similar fields with 5 years experience or MS in Computer science or similar fields with 3 years experience, with training and work experience in LLM/ NLP and search. Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments. Experience in machine learning frameworks, ML Ops tools and practices. Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, Cloud. Formation)Proficient in building AI Agents (e.g., Lang. Chain, Lang. Graph, Auto. Gen), integration of tools (e.g., API) and RAG based solutions (e.g., open search) Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/ CD) Preferred qualifications, capabilities, and skills. Optional, great to have - experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems).