Tiger Analytics is looking for experienced GenAI 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 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.RequirementsResponsibilities Lead the architecture, design, and implementation of GenAI/Agentic AI 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. Architect agentic AI systems using LangChain/LangGraph, CrewAI, and OpenAI Agentic SDK Design RAG architectures with hybrid search, vector databases, and knowledge graphs Optimize multi-agent workflows using reinforcement learning, dynamic orchestration, and memory management. Deploy scalable AI solutions on AWS/GCP (SageMaker, Vertex AI, Bedrock API). An Ideal Candidate would be of someone who has-8+ years in AI/ML engineering with large-scale deployment expertise.Proficient in prompt engineering (zero-shot, chain-of-thought) and LLM evaluation.Strong background in insurance/financial domains (preferred) Agile collaborator with GitHub/VS Code proficiency BenefitsThis position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Tiger Analytics is looking for experienced GenAI 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 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/Agentic AI 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.
- Architect agentic AI systems using LangChain/LangGraph, CrewAI, and OpenAI Agentic SDK
- Design RAG architectures with hybrid search, vector databases, and knowledge graphs
- Optimize multi-agent workflows using reinforcement learning, dynamic orchestration, and memory management.
- Deploy scalable AI solutions on AWS/GCP (SageMaker, Vertex AI, Bedrock API).
- An Ideal Candidate would be of someone who has-
8+ years in AI/ML engineering with large-scale deployment expertise.
Proficient in prompt engineering (zero-shot, chain-of-thought) and LLM evaluation.
Strong background in insurance/financial domains (preferred)
Agile collaborator with GitHub/VS Code proficiency
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.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
