GenAI Engineer
Tiger Analytics Inc.9 months ago
Remote, CanadaSenior
Responsibilities
- Design, build, and deploy end-to-end generative AI and agentic AI solutions.
- Develop and orchestrate multi-agent workflows using LangGraph, MCP, and A2A communication patterns.
- Fine-tune large language models using supervised fine-tuning, RLHF, and other advanced techniques.
- Apply reinforcement learning to optimize agent behavior, decision-making, and long-horizon tasks.
- Design experimentation frameworks with offline and online evaluations, A/B testing, and metric-driven improvements.
- Implement retrieval augmentation, grounding, validation layers, confidence scoring, and self-reflection to reduce hallucinations.
- Integrate GenAI solutions into production systems in collaboration with data engineering, product, and platform teams.
- Monitor and continuously improve model performance, reliability, latency, and cost.
Requirements
- 5+ years of industry experience in software engineering, machine learning, or AI-focused roles.
- Strong hands-on experience with LangGraph and agentic workflows.
- Practical experience with MCP and A2A system design.
- Proven experience fine-tuning LLMs using supervised fine-tuning and reinforcement learning-based methods.
- Strong understanding and application of reinforcement learning in production or research settings.
- Background in experimental design, model evaluation, and statistical analysis.
- Ability to reduce hallucinations using techniques beyond creative prompting.
- Proficiency in Python and modern ML/AI frameworks.
Benefits
- Significant career development opportunities.
- Remote, full-time position.
- Opportunity to work in a small, fast-growing, challenging, and entrepreneurial environment with substantial individual responsibility.
Tech Stack
Categories
About Tiger Analytics Inc.
Tiger Analytics Inc. provides data and AI consulting services that deliver machine learning, analytics, and cloud data engineering solutions for large enterprises across industries, including life sciences. The company engages on strategy and implementation projects, from modern BI and data platforms to MLOps, helping Fortune 100 clients turn data into business outcomes. Founded in 2011 and headquartered in Santa Clara, it is privately held with operations across North America, Europe, and Asia-Pacific.