Gen AI Engineer

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 & solutions to empower businesses to achieve real outcomes and value at scale. We 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.

Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are a Great Place to Work-Certified™ company, recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG, and others.

We are looking for a highly skilled 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.

Requirements Key Requirements Experience: Minimum of 7+ years of professional experience in software development and AI engineering

Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers

Infrastructure & DevOps: Experience with DevOps, 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

Core Focus Areas & Expectations 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 LangChain, 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, TruLens) to assess performance, grounding accuracy, and hallucination detection

Ability to iterate systems based on performance metrics and continuous improvement practices

Benefits Significant career development opportunities exist as the company grows.

The position offers a unique opportunity to be part of a small, fast-growing, challenging and 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.

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