Keysight is a mission-critical design enablement partner for organizations solving the world’s most complex engineering challenges. With deep engineering expertise and leading design, emulation, and test solutions, our ~16,800 employees help customers in over 100 countries accelerate innovation across communications, automotive, energy, quantum, aerospace and defense, semiconductor, and artificial intelligence markets. Learn more about what we do.

At Keysight, people come together to explore new ideas, challenge what's possible, and advance the technologies defining the future. Here, you'll find opportunities to do your best work, take your career further, and thrive in an award-winning culture. Learn more about our benefits.

Responsibilities

We are seeking an AI Architect / Enterprise Architect to design, govern, and scale Agentic AI solutions that drive measurable productivity improvements across HR, Finance, Sales, Services, and Employee Experience functions.

This role will lead the enterprise architecture, agent orchestration strategy, and platform design for AI-powered workflows, autonomous agents, copilots, and decision-support systems, ensuring alignment with business outcomes, security, compliance, and enterprise standards.

You will work closely with business leaders, product teams, data engineering, security, and IT to translate enterprise use cases into production-grade agentic AI systems.

Key Responsibilities

Enterprise & AI Architecture

• Define the enterprise architecture for Agentic AI platforms, including LLMs, AI agents, tools, workflows, memory, orchestration, and observability
• Design scalable architectures for multi-agent systems, human-in-the-loop workflows, and autonomous task execution
• Establish reference architectures, patterns, and guardrails for AI productivity use cases
• Align AI architecture with enterprise IT, data, security, and cloud strategies

Agentic AI & Productivity Use Cases

• Lead AI solution design for enterprise productivity across HR, Finance, Sales, Services and Employee Experience.
• Translate business problems into agent-based workflows with clear ROI and KPIs
• Design copilots, autonomous agents, and AI assistants integrated with enterprise systems

Platform, Data & Integration

• Architect integrations with enterprise systems (e.g., SAP SuccessFactors, Oracle (ERP, GTM, OTM), Salesforce, ServiceNow, CPQ)
• Define data pipelines, vector stores, retrieval strategies (RAG), and memory architectures
• Select and govern LLMs, embeddings, tools, and frameworks (open-source and commercial)
• Design API-first (MCP), event-driven architectures for AI services

Governance, Security & Compliance

• Establish AI governance, responsible AI, and risk management frameworks
• Ensure compliance with data privacy, security, and regulatory requirements
• Define controls for prompt management, model evaluation, auditability, and monitoring
• Partner with security and legal teams on AI risk assessments

Leadership & Stakeholder Engagement

• Act as a trusted advisor to business and technology leaders
• Lead architecture reviews and guide delivery teams
• Influence AI strategy, roadmap, and investment decisions
• Mentor teams on agentic AI best practices and emerging patterns

Qualifications

Required Qualifications

Technical Expertise

• Strong experience in enterprise architecture, solution architecture, or AI architecture
• Hands-on knowledge of Agentic AI concepts (autonomous agents, planning, tool use, memory, orchestration, MCP)
• Experience with LLMs and GenAI platforms (OpenAI, Azure OpenAI, AWS Bedrock, Google, open-source models)
• Expertise in RAG architectures, vector databases, and knowledge systems
• Solid understanding of cloud-native architectures (AWS, Azure, GCP)

Enterprise Systems & Productivity

• Experience integrating AI with HR, Finance, Sales, and Service platforms
• Understanding of enterprise workflows, business processes, and productivity metrics
• Strong API, MCP,  microservices, and integration design experience

Architecture & Governance

• Experience defining architecture standards, reference models, and governance frameworks
• Knowledge of security, identity, access control, and data privacy in AI systems
• Ability to balance innovation with enterprise risk and compliance

Preferred Qualifications

• Experience delivering AI productivity transformations at enterprise scale
• Familiarity with agent frameworks (MCP, LangGraph, AutoGen, CrewAI, Semantic Kernel, etc.)
• Experience with AI tools and observability
• Background in enterprise transformation programs