Agentic AI Engineer - RL

ABOUT XENONSTACK

XenonStack is the fastest-growing Data and AI Foundry for Agentic Systems, enabling people and organizations to gain real-time and intelligent business insights.

We deliver innovation through:

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  Akira AI – Building Agentic Systems for AI Agents

• XenonStack Vision AI – Vision AI Platform

• NexaStack AI – Inference AI Infrastructure for Agentic Systems

Our mission is to accelerate the world’s transition to AI + Human Intelligence, combining reasoning, perception, and action to create enterprise-ready AI agents.

THE OPPORTUNITY

We are seeking an Agentic AI Engineer (Specialized in Reinforcement Learning) with 2–5 years of experience in applying RL to enterprise-grade systems. This role involves designing and deploying adaptive AI agents that continuously learn, optimize decisions, and evolve in dynamic environments.

You’ll work at the intersection of RL research, agentic orchestration, and real-world enterprise workflows — building agents that do more than automate, but truly reason, adapt, and improve over time.

JOB ROLES AND RESPONSIBILITIES

Reinforcement Learning Development

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  Design, implement, and train RL algorithms (PPO, A3C, DQN, SAC) for enterprise decision-making tasks.

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  Develop custom simulation environments to model business processes and operational workflows.

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  Experiment with reward function design to balance efficiency, accuracy, and long-term value creation.

Agentic AI System Design

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  Build production-ready RL-driven agents capable of dynamic decision-making and task orchestration.

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  Integrate RL models with LLMs, knowledge bases, and external tools for agentic workflows.

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  Implement multi-agent systems to simulate collaboration, negotiation, and coordination.

Deployment & Optimization

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  Deploy RL agents on cloud and hybrid infrastructures (AWS, GCP, Azure).

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  Optimize training and inference pipelines using distributed computing frameworks (Ray RLlib, Horovod).

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  Apply model optimization techniques (quantization, ONNX, TensorRT) for scalable deployment.

Evaluation & Monitoring

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  Develop pipelines for evaluating agent performance (robustness, reliability, interpretability).

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  Implement fail-safes, guardrails, and observability for safe enterprise deployment.

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  Document processes, experiments, and lessons learned for continuous improvement.

SKILLS REQUIREMENTS

Technical Skills

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  2–5 years of hands-on experience with Reinforcement Learning frameworks (Ray RLlib, Stable Baselines, PyTorch RL, TensorFlow Agents).

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  Strong programming skills in Python; proficiency with PyTorch / TensorFlow.

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  Experience designing and training RL algorithms (PPO, DQN, A3C, Actor-Critic methods).

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  Familiarity with simulation environments (Gymnasium, Isaac Gym, Unity ML-Agents, custom simulators).

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  Experience in reward modeling and optimization for real-world decision-making tasks.

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  Knowledge of multi-agent systems and collaborative RL is a strong plus.

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  Familiarity with LLMs + RLHF (Reinforcement Learning with Human Feedback) is desirable.

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  Exposure to cloud platforms (AWS/GCP/Azure), containers (Docker, Kubernetes), and CI/CD for ML.

Professional Attributes

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  Strong analytical and problem-solving mindset.

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  Ability to balance research depth with practical engineering for production-ready systems.

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  Collaborative approach, working across AI, data, and platform teams.

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  Commitment to Responsible AI (bias mitigation, fairness, transparency).

XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT!

At XenonStack, we believe in shaping the future of intelligent systems. We foster a culture of cultivation built on bold, human-centric leadership principles, where deep work, simplicity, and adoption define everything we do.

Our Cultural Values

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  Agency – Be self-directed and proactive.

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  Taste – Sweat the details and build with precision.

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  Ownership – Take responsibility for outcomes.

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  Mastery – Commit to continuous learning and growth.

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  Impatience – Move fast and embrace progress.

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  Customer Obsession – Always put the customer first.

Our Product Philosophy

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  Obsessed with Adoption – Making AI agents accessible and enterprise-ready.

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  Obsessed with Simplicity – Turning complex RL + agentic challenges into intuitive, reliable systems.

Be part of our mission to reimagine adaptive, enterprise-grade AI agents with Reinforcement Learning and accelerate the world’s transition to AI + Human Intelligence.

WHY SHOULD YOU JOIN US?