Job Details

Overview

Tiger Analytics is looking for 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 has been recognized by market research firms, including Forrester and Gartner.

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.
• Experience architecting GenAI/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).
• Ideal candidate 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.

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.