Tiger Analytics Inc.
GenAI Engineer
Remote role where the employee must remain based in a particular country.
Canada only
Employer listed it 8 months ago · Found 1h ago
Been open since 8 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
Canada only
Timezone
US East
Contract
Full-time
Experience
Mid
Category
Software
This employer didn't state pay. Jobs like this usually pay around $145k–$245k a year, a typical range taken from 592 mid-level software roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Work from home
This is a remote role, but the employee must be based in Canada. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "Canada, Remote"
What Nomaders makes of it
- Residency required in Canada
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
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.
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.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Tiger Analytics Inc., mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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