About Xenonstack XenonStack is a Data and AI Foundry for Agentic Systems, enabling enterprises to design, deploy, operate, and scale intelligent agents across digital and physical environments.

About Xenonstack XenonStack is a Data and AI Foundry for Agentic Systems, enabling enterprises to design, deploy, operate, and scale intelligent agents across digital and physical environments.

We Build Enterprise-grade Platforms Across The Agentic Stack

- Akira AI — Reasoning and agent orchestration. Turn models into collaborative, policy-governed agents that learn and act together.
- ElixirData — Agentic analytics intelligence. Explainable, decision-centric analytics for measurable business outcomes.
- NexaStack — Agentic infrastructure automation. Secure, compliant AI deployment across cloud, edge, and on-prem.
- MetaSecure — Trust, compliance and defense. Continuous assurance with AI-BOMs, risk scoring, and agentic security.

Our mission is to accelerate the world’s transition to AI + Human Intelligence by making agentic systems reliable, responsible, and enterprise-ready.

THE OPPORTUNITY

We are seeking an Machine Learning Engineer, Model Evaluation to ensure that large language models (LLMs) and agentic AI systems meet enterprise-grade standards of accuracy, safety, and trustworthiness .

This role focuses on evaluating, benchmarking, and stress-testing LLMs in real-world workflows, building frameworks for reliability, robustness, and continuous improvement . If you thrive at the intersection of AI research, applied testing, and responsible deployment , this is the role for you.

Key Responsibilities

- Evaluation Frameworks
- Design and implement LLM evaluation pipelines covering accuracy, robustness, safety, and bias.
- Develop automated systems for benchmarking models on enterprise-relevant tasks.

- Reliability Engineering

- Conduct stress tests, adversarial testing, and edge-case evaluations.
- Build tools to measure latency, consistency, and error recovery in multi-turn interactions.

- Metrics & Monitoring





- Define KPIs such as factual accuracy, hallucination rate, toxicity, and compliance alignment.
- Establish real-time monitoring for drift, anomalies, and performance regressions.

- Collaboration & Alignment

- Partner with ML engineers, product managers, and domain experts to align evaluation with business objectives.
- Work with Responsible AI teams to implement ethical, explainable, and compliant evaluation practices.

- Continuous Improvement

- Feed insights from evaluation into fine-tuning, RLHF/RLAIF pipelines, and model selection.
- Maintain a central repository of test cases, benchmarks, and evaluation results.

- Research & Innovation

- Stay current with state-of-the-art LLM evaluation techniques, from academic benchmarks to applied enterprise metrics.
- Explore automated evaluation using agentic test harnesses and synthetic data generation.

Skills & Qualifications

Must-Have

- 3––6 years in AI/ML, NLP, or applied model evaluation.
- Strong understanding of LLM architectures, prompt engineering, and failure modes.
- Hands-on with evaluation frameworks (Eval harnesses, Ragas, OpenAI Evals, DeepEval).
- Proficiency in Python and libraries like LangChain, LangGraph, LlamaIndex, Hugging Face.
- Experience with vector databases, RAG pipelines, and knowledge graph integration.
- Familiarity with bias/fairness testing and Responsible AI frameworks.

Good-to-Have

- Experience with reinforcement learning (RLHF, RLAIF) and reward modeling.
- Exposure to agentic evaluation frameworks (multi-agent stress testing, synthetic user simulators).
- Knowledge of compliance and safety requirements for BFSI, GRC, or SOC use cases.




- Contributions to open-source evaluation libraries or research papers.

WHY SHOULD YOU JOIN US?

- Agentic AI Product Company

Ensure reliability in cutting-edge AI platforms that are redefining enterprise adoption.

- A Fast‑Growing Category Leader

Be part of one of the fastest-growing AI Foundries , powering Fortune 500 enterprises with trustworthy AI.

- Career Mobility & Growth

Grow into roles such as AI Systems Architect, Responsible AI Engineer, or Reliability Engineering Lead .

- General Exposure

Work on enterprise-scale evaluation challenges across BFSI, Healthcare, Telecom, and GRC.

- Create Real Impact

Your evaluations will directly shape production-grade AI agents used in mission-critical systems .

- Culture of Excellence

Our values — Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession — empower you to innovate fearlessly.

- Responsible AI First

Join a company that prioritizes trustworthy, explainable, and compliant AI .

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

- 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 accessible, reliable, and enterprise-ready.
- Obsessed with Simplicity – Turning complex evaluation challenges into seamless, automated frameworks.

Be part of our mission to accelerate the world’s transition to AI + Human Intelligence — by making AI agents not just powerful, but trustworthy and reliable .

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📌 Machine Learning Engineer, Model Evaluation (San Martín)
🏢 XenonStack Moments
📍 San Martín