Senior Staff AI Engineer

About JazzX AI: 
  Vision: Enterprises operating on institutional intelligence—governed, self-improving, and scalable beyond individual expertise.

JazzX AI is defining the future of enterprise work—by building AI-native digital workers that actually get the job done.   We believe enterprises don't scale expertise—they lose it. Knowledge stays trapped in individuals, judgment gets applied inconsistently, and the best talent spends time on work that should run itself. We're changing that. 

JazzX AI transforms messy enterprise reality into institutional intelligence: governed digital workers that capture expert judgment, make every decision explainable, and continuously improve through real-world execution. The result is faster decisions, higher-quality outcomes, and reliable execution at scale—in domains where getting it wrong isn't an option.   We're starting with lending and due-diligence workflows—complex, regulated, high-stakes. From here, we're building the backbone for enterprise intelligence across industries.   This is early-stage, hard, and consequential work. If you want to be part of bringing AI systems to market that actually run in production, handle real complexity, and deliver real outcomes—not demos, not chatbots—JazzX AI is the place.
Headquartered in Los Altos, CA. Backed by SAIGroup.   About SAIGroup :   SAIGroup a private investment firm that has committed $1B to build and scale next-generation, AI-powered enterprise software companies. SAIGroup’s portfolio serves 2,000+ global enterprise customers, generates nearly $800M in annual revenue, and employs 4,000+ people worldwide — providing JazzX AI with long-term capital, deep operating expertise, and access to real-world enterprise scale from day one.

Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai

Learn more about SAIGroup:
Website: https://saigroup.ai

 

 

About the Role

We are seeking an experienced AI Engineer with deep expertise in Reinforcement Learning (RL) to join our team as a Senior Staff Architect. In this role, you will be responsible for shaping the vision, architecture, and technical execution of RL-driven AI reasoning models and systems that power next-generation enterprise AGI platform.

You will lead the design, development, and optimization of cutting-edge RL solutions, from experimentation and simulation through production deployment. This includes building scalable training architectures, architecting multi-agent and hierarchical RL frameworks, and ensuring that the RL systems are resilient, efficient, explainable and safe.

As a senior technical leader, you will partner with cross-functional teams—including product, core platform engineering, and research—to define architectural best practices, establish governance standards, and enable seamless integration of RL into our broader AGI platform. You will also drive innovation by exploring novel RL techniques, mentoring engineers and researchers, and ensuring the RL infrastructure can scale to support high-throughput training and real-world scenarios and enterprise use cases end to end.

Ultimately, your work will be critical in bridging research and production, ensuring that the latest RL advancements translate into reliable, impactful, and enterprise-ready AI solutions.

Key Responsibilities

• Architecture & Design: Define and drive the end-to-end architecture for reinforcement learning–based systems, including training pipelines, simulation environments, reward shaping, and model serving.
• Research & Development: Apply cutting-edge RL techniques (policy optimization, model-based RL, hierarchical RL, multi-agent RL, etc) to solve complex enterprise problems.
• Scalability & Infrastructure: Design distributed training systems, leverage cloud-native infrastructure, and optimize for performance, reproducibility, and cost-efficiency.
• Leadership & Mentorship: Provide technical leadership to AI engineers and researchers; mentor junior team members; review designs and code with a focus on scalability, robustness, and clarity.
• Collaboration: Partner with product, data, and platform teams to ali