Full Stack Gen AI Engineer

Overview

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services and solutions to empower businesses to achieve real outcomes and value  are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.

We are looking for a highly skilled Full Stack Gen AI Engineer with 7+ years of experience in software engineering, with a heavy focus on Python, AWS infrastructure, and Generative AI. The ideal candidate will be responsible for building high-performance API services and implementing complex RAG and Agentic AI architectures.

• Experience:
  
  Minimum of 7+ years of professional experience in software development and AI engineering
• API & Backend:
  Expert in building high-performance API / microservices using Python (FastAPI) deployed on AWS Fargate (ECS) (Most Critical)
• Generative AI Integration:
  Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers
• Infrastructure & Dev Ops:
  Experience with Dev Ops, CI/CD pipelines, and ML pipelines within the AWS ecosystem
• Agentic AI:
  Exposure to building Gen AI/Agentic AI applications, managing efficiency, latency, and backend infrastructure
• Technical Standards:
  Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration
• Preferred
  
  Skills:
  
  Experience working with Bedrock Agent/Core services is a significant plus

Candidates will be expected to demonstrate deep technical proficiency in the following areas:

• Retrieval-Augmented Generation (RAG)
• Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators
• Expertise in latency optimization and relevance tuning to ensure production-grade performance
• Strategic approach to document chunking and embedding, balancing granularity with semantic coherence
• Agent Development
• Practical experience developing autonomous or semi-autonomous agents using frameworks such as Lang Chain, CrewAI, or Semantic Kernel
• Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs
• Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing
• Evaluation and Optimization
• Familiarity with evaluation frameworks (e.g., RAGAS, Tru Lens) to assess performance, grounding accuracy, and hallucination detection
• Ability to iterate systems based on performance metrics and continuous improvement practices

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. Every individual comes with a different set of skills and qualities, so even if you don t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow.

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.