Gen AI Engineer
Tiger Analytics Inc. Open · verified Oct 22, 2026 At a glance
Mid-level AI Engineering role at Tiger Analytics Inc. Remote, Canada · full-time · no salary stated · we estimate CA$100,000–CA$150,000 across Canada.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build high-throughput API services and implement complex retrieval-augmented generation and agent-based AI systems
- Create RAG pipelines with retrievers, vector stores and generators, then tune chunking, relevance and latency
- Develop agents that connect tools and external APIs, manage conversation context and handle unpredictable outputs
- Evaluate grounding, hallucinations and system performance, then use metrics to guide improvements
- Connect language-model APIs with AWS services and support delivery through CI/CD and machine-learning pipelines
What you bring
- At least seven years in software development and AI engineering, with strong Python skills
- Hands-on work integrating generative AI APIs, including AWS Bedrock, and other model providers
- Experience with AWS-based DevOps, CI/CD and machine-learning pipelines
- A solid grasp of OpenAI API conventions, JSON REST design and language-model orchestration
Who this fits
This remote role in Canada suits an experienced engineer focused on Python, AWS and generative AI systems. You’ll take on substantial individual responsibility. Familiarity with Bedrock Agent or Core services is an advantage.
From the employer
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
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.
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.