Tiger Analytics
Tiger Analytics is looking for an experienced Machine Learning Architect 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 have been recognized by various market research firms, including Forrester and Gartner.
We are seeking a hands-on Engineering Lead with deep expertise in Generative AI (GenAI), Large Language Models (LLM), and Small Language Models (SLM). The candidate will lead the design, development, and integration of AI-powered components into real-world, production-grade applications. This role requires strong engineering leadership, best practices, a practical approach to application development with applied AI, fluency in modern AI tools and frameworks, cloud-native stacks, and preferably healthcare domain knowledge. The candidate will oversee the technical delivery of AI features across various healthcare use cases, ensuring compliance with enterprise standards.
Responsibilities
Lead the architecture, design, and implementation of GenAI/Agentic AI solutions into enterprise applications.
Collaborate with AI/ML teams to operationalize models using APIs, embeddings, vector databases, and prompt engineering techniques.
Own the full-stack development and integration of GenAI features into web and 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.
Mentor engineers, oversee code reviews, architectural decisions, and DevOps practices.
Evaluate emerging GenAI tools and frameworks (e.g., OpenAI, LangChain) and recommend build-vs-buy options.
Oversee application development, testing, and deployment processes.
Requirements
10+ years of full-stack application engineering experience, with at least 2 years leading cross-functional teams.
Experience architecting agentic AI systems using LangChain, CrewAI, and OpenAI SDKs.
Designing RAG architectures with hybrid search, vector databases, and knowledge graphs.
Optimizing multi-agent workflows with reinforcement learning, orchestration, and memory management.
Deploying scalable AI solutions on AWS or GCP (SageMaker, Vertex AI, Bedrock API).
8+ years in AI/ML engineering with large-scale deployment expertise.
Proficiency in prompt engineering (zero-shot, chain-of-thought) and LLM evaluation.
Strong background in insurance or financial domains (preferred).
Agile collaboration skills with GitHub and VS Code proficiency.
This position offers excellent career development opportunities in a dynamic and entrepreneurial environment with significant individual responsibility.
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