Senior applied ai engineer – developer productivity & sdlc - keysight technologies (barcelona)

Senior Applied AI Engineer – Keysight AI Labs

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Keysight’s AI Labs is a global R&D group pioneering the integration of machine learning, generative AI into Keysight’s test, measurement, and design solutions. Our mission is to transform how engineers design, simulate, and validate advanced systems—from 6G and semiconductors to quantum and automotive—by embedding AI throughout our workflows.
About the Team

Join Keysight's central AI Hub in the heart of Barcelona. Software and AI Labs (SAL) drives innovation across Keysight’s global software engineering organization. The team focuses on accelerating developer productivity, modernizing engineering workflows, and ensuring secure, compliant adoption of emerging AI technologies.
About the Role

This role sits at the intersection of AI, software engineering, and enterprise transformation. As a Senior Applied AI Engineer, you will design and implement AI-driven solutions that modernize and accelerate Keysight’s Secure Software Development Lifecycle (SDLC). You will evaluate emerging AI technologies (LLMs, RAG, agentic systems), translate governance into practical engineering standards, and build reference architectures that can scale across integral engineering teams.
Responsibilities

Lead technical evaluations and enterprise rollouts of AI tools and platforms.
Design reusable solution patterns (prompt libraries, RAG architectures, agent workflows) to improve coding, testing, documentation, and planning.
Develop reference implementations (“golden paths”) integrating AI into DevSecOps toolchains.
Evaluate emerging AI paradigms (e.g., MCP, agentic frameworks) and guide safe adoption.
Architect end-to-end AI solutions spanning cloud, on-prem, and hybrid environments.
Optimize AI integrations for performance, cost efficiency, and developer experience.
Collaborate with engineering and DevSecOps teams to embed AI into CI/CD, testing, and release processes.
Translate corporate AI governance into practical engineering guardrails.
Align AI practices with ISO/IEC 42001, NIST AI RMF, SOC2, and OWASP API Security principles.
Implement secure data handling, model access control, and vendor usage standards.
Engage engineering leaders and IT stakeholders to drive adoption programs.
Manage vendor evaluations, pilots, and compliance alignment.
Provide executive-level updates on AI adoption impact, productivity gains, and risks.
Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
5–10+ years of experience in software engineering.
Hands‑on experience applying modern AI technologies (LLMs, RAG, agent frameworks) to real‑world engineering workflows.
Experience integrating AI into DevSecOps environments and CI/CD toolchains.
Working knowledge of secure software development practices and practical security controls.
Strong communication skills with experience influencing cross‑functional teams.
Desired Qualifications

Experience defining enterprise engineering KPIs and productivity metrics.
Exposure to ISO/IEC 42001, NIST AI RMF, SOC2, or similar compliance frameworks.
Experience with MLOps pipelines and data engineering for AI (ETL, embeddings, vector databases).
Prior experience driving enterprise AI enablement programs.
Experience working in large, global engineering organizations. xpzdshu
Keysight is an Equal Opportunity Employer.

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