Senior DevOps / Platform Engineer – Runtime Validation & Governance
Skills
About the role
Overview:
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.
Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
About the Team
Keysight’s Applied AI Autonomy Initiative is building a next-generation orchestration framework that enables AI agents to reason, adapt, and coordinate across complex engineering workflows.
The team works at the intersection of AI systems, platform engineering, and high-assurance software, focusing on how autonomous systems can be safely validated, governed, and deployed into production environments used by engineers worldwide.
Our Barcelona R&D hub brings together experienced engineers, researchers, and system architects in a highly collaborative, international environment.
About the Role
As Senior Agentic DevOps Engineer – Runtime Validation & Governance, you will design and implement the runtime validation, control, and governance layer that determines how AI-generated logic is tested, verified, and promoted into production.
This is not a traditional DevOps role. You will work on advanced deployment and validation pipelines where autonomous agents, simulations, and safety controls are first-class citizens. Your work ensures that AI-driven orchestration remains explainable, reversible, traceable, and auditable before impacting live engineering systems.
Responsibilities:
Design sandboxed and containerised execution environments for testing AI-generated logic prior to deployment
Build and maintain multi-stage validation and release pipelines (sandbox validation gated staging monitored production)
Define runtime health metrics, confidence thresholds, and promotion gates for autonomous agent outputs
Develop regression and continuous verification frameworks to detect drift, instability, or unexpected behaviours in agent-driven workflows
Implement telemetry, observability, and traceability pipelines capturing agent decisions, validation results, and anomalies
Design snapshotting and rollback mechanisms to safely restore verified system states
Ensure auditability, reproducibility, and governance of all agent-generated artefacts
Collaborate closely with AI researchers, platform architects, safety engineers, and UI teams
Qualifications:
Required Qualifications
5+ years of experience in DevOps, platform engineering, systems engineering, or high-assurance infrastructure
Strong experience designing CI/CD pipelines for complex, production-grade systems
Proven background in sandboxing, controlled deployments, validation pipelines, or safety-critical systems
Strong programming skills in Python and C or C++
Experience with runtime monitoring, telemetry, rollback, and failure recovery mechanisms
Solid understanding of distributed systems and production reliability
Desired Qualifications
Experience with AI agent frameworks (e.g. LangGraph, LangChain, or similar)
Exposure to simulation environments, HPC systems, or digital twins
Knowledge of regression testing strategies, differential validation, or confidence-based promotion models
Background in autonomous systems, robotics, or AI governance
Experience working in regulated, high-assurance, or safety-critical environments
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