Generative AI Leader/Architect

Job Description

Generative AI Leader/Architect

Company: Tiger Analytics Inc.

Location: Dallas, TX

• Remote
  
  

Job Type: Full-time

Posted: 12 hours ago

Job Description

Tiger Analytics is seeking a GenAI Architect with expertise in Generative AI (GenAI), Large Language Models (LLM) / Small Language Models (SLM). The role involves leading the design, development, and integration of AI-powered components into real-world, production-grade applications, application development and system design with applied AI, fluency in modern AI tools, frameworks, cloud-native application stacks.

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).
• 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

Opportunity for career development in a fast-growing entrepreneurial environment.