GenAI Engineer
Tiger Analytics Inc. Open · verified Oct 24, 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.
remoteroles summary, based on the employer's posting.
What you'll do
- Build and launch generative and agent-based AI systems for practical use cases
- Coordinate multi-agent workflows with LangGraph, MCP and A2A communication patterns
- Fine-tune language models with supervised methods and reinforcement learning to improve task results and alignment
- Test model behavior through offline and live evaluations, A/B tests and metric-based iteration
- Reduce hallucinations with retrieval, grounding, validation, confidence scoring and self-review techniques
What you bring
- At least five years in software engineering, machine learning or AI-focused work
- Hands-on LangGraph experience, including building agent workflows, plus practical MCP and A2A system design
- Experience fine-tuning large language models with supervised methods and reinforcement learning
- A background in experimentation, model evaluation and statistical analysis, with Python and modern AI or ML frameworks
Who this fits
This mid-level, full-time role suits an engineer who has built and evaluated agentic AI systems and can improve their reliability beyond prompt design. The position is remote in Canada.
From the employer
Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.
We are looking for a highly skilled GenAI Engineer with strong hands-on experience in building, evaluating, and deploying advanced Generative AI systems. The ideal candidate will have deep expertise in agentic frameworks, model fine-tuning, and reinforcement learning, along with a strong focus on experimentation, reliability, and hallucination mitigation beyond prompt engineering.
Requirements
- Design, build, and deploy end-to-end Generative AI and agentic AI solutions for real-world use cases.
- Develop and orchestrate multi-agent workflows using LangGraph, MCP (Model Context Protocol), and A2A (Agent-to-Agent) communication patterns.
- Fine-tune large language models (LLMs) using supervised fine-tuning (SFT), RLHF, and other advanced techniques to improve task performance and alignment.
- Apply reinforcement learning approaches to optimize agent behavior, decision-making, and long-horizon tasks.
- Design and execute rigorous experimentation frameworks, including offline/online evaluations, A/B testing, and metric-driven improvements.
- Implement robust strategies for hallucination reduction, such as retrieval augmentation, grounding, validation layers, confidence scoring, and self-reflection mechanisms.
- Collaborate with data engineers, product managers, and platform teams to integrate GenAI solutions into production systems.
- Monitor, evaluate, and continuously improve model performance, reliability, latency, and cost.
- Stay up to date with the latest research and advancements in GenAI, agentic systems, and model alignment.
Required Qualifications
- 5+ years of industry experience in software engineering, machine learning, or AI-focused roles.
- Strong hands-on experience with LangGraph and building agentic workflows.
- Practical experience with MCP (Model Context Protocol) and A2A (Agent-to-Agent) system design.
- Proven experience in fine-tuning LLMs, including supervised fine-tuning and reinforcement learning-based methods.
- Solid understanding and application of reinforcement learning concepts in production or research settings.
- Strong background in experimental design, model evaluation, and statistical analysis.
- Demonstrated ability to reduce hallucinations using techniques beyond creative prompting.
- Proficiency in Python and experience with modern ML/AI frameworks.
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.
AI Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
AI EngineeringRemote
Find me workBy the team behind remoteroles.