GenAI Engineer

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 skilledGenAI Engineerwith 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 usingLangGraph,MCP (Model Context Protocol), andA2A (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.
• Applyreinforcement learningapproaches to optimize agent behavior, decision-making, and long-horizon tasks.
• Design and execute rigorousexperimentation frameworks, including offline/online evaluations, A/B testing, and metric-driven improvements.
• Implement robust strategies forhallucination 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 experiencein software engineering, machine learning, or AI-focused roles.
• Strong hands-on experience withLangGraphand building agentic workflows.
• Practical experience withMCP (Model Context Protocol)andA2A (Agent-to-Agent)system design.
• Proven experience infine-tuning LLMs, including supervised fine-tuning and reinforcement learning-based methods.
• Solid understanding and application ofreinforcement learningconcepts in production or research settings.
• Strong background inexperimental 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.