XenonStack is the fastest-growing Data and AI Foundry for Agentic Systems, enabling enterprises to gain real-time, intelligent business insights and operational resilience.
We innovate through:
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 by building intelligent, trustworthy, and adaptive AI systems for enterprises.
We are seeking a passionate AI Researcher with a strong foundation in machine learning, reinforcement learning, and large language models (LLMs) to advance our research in Agentic AI systems.
In this role, you will work closely with product and engineering teams to explore next-generation architectures, reasoning models, multimodal intelligence, and reinforcement-based optimization — helping shape how enterprises deploy and trust AI agents in production.
If you thrive at the intersection of theory, experimentation, and scalable systems, and are driven to solve foundational problems in AI, this is the role for you.
Core Research
Conduct applied research on large language models, reasoning systems, and multi-agent architectures.
Explore and prototype reinforcement learning, retrieval-augmented generation (RAG), and hierarchical memory systems for enterprise contexts.
Design, run, and evaluate experiments to improve context management, generalization, and reasoning accuracy.
Contribute to internal research publications, model evaluation reports, and open-source initiatives.
Applied Development
Collaborate with engineering teams to translate research into deployable prototypes.
Build and evaluate agentic frameworks and orchestration strategies using LangChain, LangGraph, or equivalent.
Develop and test AI safety and interpretability techniques to ensure ethical and reliable model behavior.
Work on integrating research advancements into real-world AI applications and products.
Collaboration & Impact
Work cross-functionally with ML engineers, data scientists, and AI product teams.
Present findings in internal research forums and contribute to thought leadership.
Stay current with emerging research in LLMs, RLHF, multimodal AI, and agentic reasoning.
Must-Have
Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related field.
3–6 years of research experience in AI, ML, or NLP domains.
Strong expertise in deep learning frameworks (PyTorch, TensorFlow, JAX).
Experience with LLMs, Transformers, RAG pipelines, and reinforcement learning (RLHF, RLAIF).
Proficiency in Python and ML research tooling (Weights & Biases, Hugging Face, LangChain).
Ability to design, conduct, and analyze experiments with rigor.
Good-to-Have
Research experience in multi-agent systems, symbolic reasoning, or causal inference.
Understanding of evaluation metrics for LLMs and AI safety principles.
Contributions to AI research papers, open-source projects, or conferences (NeurIPS, ICLR, ICML, ACL).
Familiarity with distributed training and optimization at scale.
Work Closely with Leadership – Collaborate with the CTO and Chief Scientist on next-generation AI architecture design.
High-Impact Research – Your work will directly influence how enterprises adopt, trust, and scale AI agents.
Career Growth – Progress into roles such as Principal AI Scientist, Research Lead, or AI Architect.
Global Exposure – Partner with Fortune 500 clients, research collaborators, and AI ecosystems worldwide.
Culture of Excellence – Our values — Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession — empower you to lead with innovation and rigor.
Responsible AI First – Contribute to building ethical, explainable, and robust AI systems at scale.
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
Agency – Be self-directed and proactive.
Taste – Sweat the details and build with precision.
Ownership – Take responsibility for outcomes.
Mastery – Commit to continuous learning and growth.
Impatience – Move fast and embrace progress.
Customer Obsession – Always put the customer first.
Our Product Philosophy
Obsessed with Adoption – Making AI agents enterprise-ready and accessible.
Obsessed with Simplicity – Turning complex AI research into intuitive, reliable systems.
Be part of our mission to accelerate the world’s transition to AI + Human Intelligence — by building the foundation for responsible, autonomous, and adaptive Agentic AI.
