{"id":3131013,"url":"https://alion.io/job/keysight-senior-ai-systems-engineer-architect","title":"Senior AI Systems Engineer / Architect","company":{"id":53596,"name":"Keysight","domain":"keysight.com","url":"https://alion.io/company/keysight","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":81,"open_postings":108,"ghost_share":0,"stale_share":0.741,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Rosa, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":156740,"max":261230,"currency":"USD","period":"year","gross":null,"usd_annual":261230},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"gRPC","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Rest API","optional":false},{"name":"Digital Twin","optional":true},{"name":"Docker","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Kubernetes","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multimodal AI","optional":true}],"status":"live","first_seen_at":"2026-10-23T02:36:00Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-28T17:14:45Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"OverviewCSG AI is building advanced AI systems for Keysight CSG that bring together agentic reasoning, machine learning, reinforcement learning, engineering software, simulation, emulation, measurement, and product integration to transform how complex engineering designs are explored, evaluated, and improved.\nOur ambition is to move beyond isolated AI assistants and point solutions. We are building systems that can understand engineering intent, reason across tools and data, coordinate specialized capabilities, act on virtual and physical engineering environments, and learn from the results.\nThe goal is a foundation for AI-driven engineering at scale, where intelligent systems can connect design intent to simulation, emulation, instruments, measurements, and product workflows, helping engineers explore larger design spaces and turn complex workflows into repeatable, adaptive, and increasingly autonomous capabilities.\nResponsibilities\nRole Overview\nAs a Senior AI Systems Engineer / Architect, you will define and build the architectural backbone that connects AI reasoning with Keysight engineering tools, data, models, services, and products. You will design how agents represent state and context, coordinate work, invoke tools, exchange structured information, and interact with engineering environments.\nYour systems will span the full fidelity spectrum, from software simulators and digital models, through real-time and hardware-in-the-loop emulators, to instruments, measurement systems, lab automation, and physical test workflows. You will create the integration patterns that allow AI capabilities to operate coherently across these environments rather than as isolated prototypes.\nThis is a hands-on architecture and systems engineering role. You will shape core agentic abstractions while also building production-quality software, APIs, orchestration services, tool interfaces, and backend integrations. You will work closely with ML, RL, Agentic DevSecOps, product, and domain teams to turn advanced AI capabilities into engineering systems that are powerful, extensible, reliable, and ready to become part of Keysight products and workflows.\nKey Responsibilities\nArchitect and implement the core agentic systems that connect LLMs and other reasoning models with engineering tools, APIs, data services, learned models, policies, and product workflows.\nDesign orchestration and multi-agent reasoning flows using graph-based, tool-calling, or equivalent architectures, including clear semantics for state, context, memory, coordination, and execution.\nBuild backend services, APIs, SDKs, and integration layers that allow intelligent systems to invoke engineering capabilities, retrieve context, execute multi-step workflows, and return structured, verifiable results.\nIntegrate AI systems with Keysight CSG engineering environments across design, simulation, emulation, physical measurement, test automation, laboratory systems, and product software.\nDefine robust agent and tool contracts, structured schemas, validation interfaces, state models, and error handling patterns that support predictable and extensible execution.\nDesign context, retrieval, memory, and persistence mechanisms that allow AI systems to reason over engineering intent, product knowledge, design artifacts, simulation and emulation results, measurement data, and workflow history.\nBuild production-quality orchestration services with modular architecture, versioning, observability, tracing, auditability, and clear failure and recovery behavior.\nCreate reusable integration patterns for connecting AI systems with existing engineering platforms, enterprise services, data pipelines, compute environments, and product software.\nCollaborate with product, UX, and application teams to turn agentic capabilities into compelling engineering experiences through product features, operator workflows, APIs, and intelligent assistants.\nPartner with Agentic DevSecOps and runtime teams so agent workflows can be validated, monitored, governed, replayed, and operated reliably in production environments.\nWork with ML and RL engineers to integrate learned models, representations, policies, evaluations, and feedback loops into larger agentic systems.\nPrototype new agentic concepts rapidly, then harden the successful ones into maintainable, testable, documented, and production-quality software components.\nDefine technical standards and architectural patterns for agent interfaces, tool integration, orchestration, APIs, context management, and product quality across CSG AI.\nQualifications\nRequired Qualifications\nBS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent industry experience.\nTypically 5+ years of relevant experience building production software systems, AI platforms, distributed applications, engineering tools, or intelligent systems, with demonstrated ownership of system architecture or complex integrations.\nStrong software engineering skills in Python and C++ or another production systems language, with the ability to move between high-level AI frameworks and lower-level engineering integrations.\nExperience architecting and building backend services, REST or gRPC APIs, SDKs, service integrations, and production software components.\nHands-on experience with LLM application development, tool-calling, agentic workflows, RAG, context management, or orchestration frameworks such as LangGraph, LangChain, or equivalent systems.\nStrong understanding of distributed systems, asynchronous execution, state management, concurrency, reliability patterns, and integration architecture.\nExperience integrating software systems with external engineering tools, data sources, compute systems, workflow engines, or enterprise platforms.\nAbility to design clean, structured interfaces for agents, tools, data exchange, validation, authorization, and error recovery.\nExperience building maintainable production software with automated testing, version control, CI/CD practices, observability, profiling, and clear technical documentation.\nAbility to translate emerging AI techniques into practical system architectures and collaborate across AI research, systems engineering, product engineering, and technical domain teams.\nPreferred Qualifications\nExperience integrating AI systems with engineering design, simulation, emulation, measurement, test automation, lab instrumentation, or other physical engineering workflows.\nExperience with Keysight or similar electronic design, validation, measurement, test, lab automation, wireless, semiconductor, or telecom engineering environments.\nExperience with Model Context Protocol (MCP), Agent-to-Agent communication, structured tool protocols, or custom agent runtime interfaces and interoperability standards.\nExperience with vector databases, knowledge graphs, semantic retrieval, multimodal context, document processing, or engineering knowledge systems.\nExperience designing product-facing AI features, copilots, autonomous engineering workflows, operator experiences, or AI-enabled engineering applications.\nExperience with GPU-backed inference, model serving, prompt and model versioning, evaluation pipelines, and performance optimization for AI workloads.\nExperience with Kubernetes, Docker, cloud-native or on-premises distributed services, observability tools, and production deployment patterns.\nFamiliarity with hardware-in-the-loop systems, digital twins, emulator control, instrument control, SCPI, VISA, measurement automation, or real-time engineering systems.\nExperience with security, authorization, policy enforcement, audit trails, validation, or governance mechanisms for AI-enabled workflows.\nBackground in high-performance computing, scientific computing, EDA, wireless systems, semiconductor workflows, electronic measurement, or other complex engineering domains.\nSanta Rosa, CA Pay Range: MIN $156,740.00 - MAX $261,230.00\nCareers Privacy Statement ***Keysight is an Equal Opportunity Employer.***\nRole Overview\nAs a Senior AI Systems Engineer / Architect, you will define and build the architectural backbone that connects AI reasoning with Keysight engineering tools, data, models, services, and products. You will design how agents represent state and context, coordinate work, invoke tools, exchange structured information, and interact with engineering environments.\nYour systems will span the full fidelity spectrum, from software simulators and digital models, through real-time and hardware-in-the-loop emulators, to instruments, measurement systems, lab automation, and physical test workflows. You will create the integration patterns that allow AI capabilities to operate coherently across these environments rather than as isolated prototypes.\nThis is a hands-on architecture and systems engineering role. You will shape core agentic abstractions while also building production-quality software, APIs, orchestration services, tool interfaces, and backend integrations. You will work closely with ML, RL, Agentic DevSecOps, product, and domain teams to turn advanced AI capabilities into engineering systems that are powerful, extensible, reliable, and ready to become part of Keysight products and workflows.\nKey Responsibilities\nArchitect and implement the core agentic systems that connect LLMs and other reasoning models with engineering tools, APIs, data services, learned models, policies, and product workflows.\nDesign orchestration and multi-agent reasoning flows using graph-based, tool-calling, or equivalent architectures, including clear semantics for state, context, memory, coordination, and execution.\nBuild backend services, APIs, SDKs, and integration layers that allow intelligent systems to invoke engineering capabilities, retrieve context, execute multi-step workflows, and return structured, verifiable results.\nIntegrate AI systems with Keysight CSG engineering environments across design, simulation, emulation, physical measurement, test automation, laboratory systems, and product software.\nDefine robust agent and tool contracts, structured schemas, validation interfaces, state models, and error handling patterns that support predictable and extensible execution.\nDesign context, retrieval, memory, and persistence mechanisms that allow AI systems to reason over engineering intent, product knowledge, design artifacts, simulation and emulation results, measurement data, and workflow history.\nBuild production-quality orchestration services with modular architecture, versioning, observability, tracing, auditability, and clear failure and recovery behavior.\nCreate reusable integration patterns for connecting AI systems with existing engineering platforms, enterprise services, data pipelines, compute environments, and product software.\nCollaborate with product, UX, and application teams to turn agentic capabilities into compelling engineering experiences through product features, operator workflows, APIs, and intelligent assistants.\nPartner with Agentic DevSecOps and runtime teams so agent workflows can be validated, monitored, governed, replayed, and operated reliably in production environments.\nWork with ML and RL engineers to integrate learned models, representations, policies, evaluations, and feedback loops into larger agentic systems.\nPrototype new agentic concepts rapidly, then harden the successful ones into maintainable, testable, documented, and production-quality software components.\nDefine technical standards and architectural patterns for agent interfaces, tool integration, orchestration, APIs, context management, and product quality across CSG AI.\nRequired Qualifications\nBS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent industry experience.\nTypically 5+ years of relevant experience building production software systems, AI platforms, distributed applications, engineering tools, or 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