Generative AI Leader

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for a hands-on Engineering Lead with deep expertise in Generative AI (GenAI), Large Language Models (LLM) / Small Language Models (SLM) who can lead the design, development, and integration of AI-powered components into real-world, production-grade applications. This role demands strong engineering leadership and best practices, a practical approach to application development and system design with applied AI, fluency in modern AI tools, frameworks, cloud-native application stacks, and preferably knowledge of healthcare domain intricacies. You will lead the technical delivery of AI-powered features for a variety of horizonal and vertical healthcare use cases— all while ensuring compliance with enterprise integration standards. Requirements Responsibilities Lead the architecture, design, and implementation of GenAI/LLM-based solutions into real-world enterprise-ready applications. Collaborate with AI/ML teams to operationalize models using APIs, embeddings, vector databases, and prompt engineering techniques. Own full-stack development and integration of GenAI features into web/mobile applications. Establish best practices for scalable, secure, and maintainable AI-powered application development. Optimize application performance , latency , and reliability of AI features in production. Drive DevOps practices for continuous delivery and monitoring of AI-enabled services in production. Mentor engineers and guide code reviews, architectural decisions, and DevOps practices. Guide engineering teams in code quality, architectural reviews, and technical mentoring. Evaluate emerging GenAI tools and LLM frameworks (OpenAI, LangChain etc.) and make build-vs-buy recommendations. Oversee application-level development, testing, and deployment. Requirements 10+ years of full-stack application engineering experience, with at least 2 years leading cross-functional teams. Proven track record developing and integrating GenAI/LLM-based features into enterprise applications. Exposure to LLM fine-tuning, RAG pipelines, or model evaluation techniques for NLP use cases Familiarity with LLM orchestration tools (LangChain, Semantic Kernel etc) and embedding/vector store technologies. Proficiency in application frameworks such as Node.js, React, Python, or Java Spring Boot Strong understanding of API development, front-end/backend integration, and cloud services (AWS, Azure, or GCP) Hands-on experience with containerization (Docker, Kubernetes) and CI/CD pipelines Strong understanding of application-level security, performance tuning, and production monitoring Nice to have - Deep knowledge of healthcare payer workflows (claims processing, member portals, benefit management, etc). Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Originally posted on Himalayas