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XenonStack is the fastest -growing Data and AI Foundry for Agentic Systems, enabling enterprises to gain real -time and intelligent business insights.
We deliver innovation through:
Agentic Systems for AI Agents â akira.ai
Vision AI Platform â xenonstack.ai
Inference AI Infrastructure for Agentic Systems â nexastack.ai
Our mission is to accelerate the world’s transition to AI + Human Intelligence by building systems that are not only powerful but also safe, transparent, and accountable.
We are seeking a Responsible AI Engineer to design and implement frameworks that ensure fairness, safety, compliance, and transparency in enterprise AI systems.
This is a high -impact role at the intersection of AI engineering, ethics, and governance. You will work on ensuring that XenonStack’s Agentic AI platforms meet enterprise and regulatory standards, while remaining reliable and trustworthy in production.
Responsible AI Frameworks
Develop and implement fairness, bias detection, and transparency frameworks for AI systems.
Define policies and guardrails for safe LLM interactions, multi -agent orchestration, and decision -making systems.
Evaluation & Monitoring
Design pipelines to monitor AI reliability, safety, and hallucination rates.
Build metrics to track bias, fairness, interpretability, and ethical compliance.
Governance & Compliance
Ensure compliance with GDPR, SOC2, HIPAA, ISO 27001, and other AI governance standards.
Collaborate with legal, compliance, and security teams to embed governance by design.
Transparency & Explainability
Implement XAI (Explainable AI) techniques to make models and agent decisions interpretable.
Provide tools and dashboards for auditing and reporting AI behavior.
Collaboration & Cross -Functional Work
Work with AI Engineers, AgentOps, and Data Architects to integrate responsible AI practices across the stack.
Partner with customers and regulators to communicate system reliability and ethical safeguards.
Continuous Improvement
Stay ahead of Responsible AI research, EU AI Act, NIST AI RMF, and global standards.
Feed evaluation results into continuous improvement loops for AI reliability and safety.
Must -Have
3–6 years in AI/ML engineering, AI governance, or AI safety research.
Strong knowledge of AI fairness, interpretability, and Responsible AI frameworks.
Hands -on with evaluation tools (OpenAI Evals, Ragas, DeepEval, Fairlearn, Aequitas).
Proficiency in Python and data analysis frameworks.
Understanding of LLM architectures, RAG pipelines, and multi -agent workflows.
Familiarity with compliance and governance standards (GDPR, SOC2, ISO, HIPAA).
Good -to -Have
Exposure to reinforcement learning (RLHF, RLAIF, reward modeling).
Experience with Responsible AI monitoring in regulated industries (BFSI, Healthcare, GRC, SOC).
Knowledge of observability platforms (Weights & Biases, Arize AI, Prometheus, OpenTelemetry).
Contributions to Responsible AI open -source projects or research.
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 Responsible AI frameworks accessible and enterprise -ready.
Obsessed with Simplicity – Turning complex ethical challenges into seamless, auditable workflows.
Be part of our mission to accelerate the world’s transition to AI + Human Intelligence — by making Responsible AI the backbone of enterprise adoption.
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