Gen AI Engineer

Tiger Analytics, LLC; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Tiger Analytics is seeking a highly skilled AI Engineer with 7+ years of software and AI engineering experience to design and build high-performance API services. The role emphasizes Generative AI, RAG pipelines, and Agentic AI architectures, with a focus on Python, AWS infrastructure, and scalable backend systems.

You will implement end-to-end RAG components, integrate vector stores, manage latency, and orchestrate LLM workflows using LangChain, Bedrock, and related tools.

Qualifications

• 7+ years of professional experience in software development and AI engineering.
• Hands-on Generative AI/LLM integration with AWS Bedrock.
• Experience with DevOps, CI/CD and ML pipelines in AWS.
• Experience building Gen AI/Agentic AI apps and scalable backend infra.
• Strong Python with OpenAI API standards, JSON REST and LLM orchestration.
• Bedrock Agent/Core services experience is a plus.

Responsibilities

• Design and implement end-to-end RAG pipelines with retrievers and vector stores.
• Develop autonomous or semi-autonomous agents and integrate tools with robust error handling.
• Evaluate system performance with frameworks like TruLens or RAGAS and iterate improvements.

Skills

Python programming

LLM integration

Cloud/AWS experience

Agentic AI

API design

Tools

AWS Bedrock

LangChain

CrewAI

Semantic Kernel

Pinecone

Weaviate

pgvector

OpenAI API

Job description

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.

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

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

1. 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.

2. 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.

3. 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.

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.