Job Description

You will join the CTAO Office, reporting to the CTO for AI and Autonomous Networks. This team is responsible for shaping Nokia’s long-term architecture and technology direction for autonomous networks, AI-native operations and the platforms required to support them.

The team works across Nokia business groups, research, product units, customers and ecosystem partners to define architecture, validate technology choices, create working proof points and guide Nokia’s evolution from product-centric automation toward horizontal, reusable autonomous network capabilities. The scope spans data management platforms, agent runtime platforms, model infrastructure, orchestration, governance, security and the architectural validation environments required to test and compare competing solution approaches.

The role may be considered at Job Grade depending on the candidate’s experience and the ongoing levelling process.

As an R&D Architect for Autonomous Networks Architecture, you will contribute to the definition, validation and evolution of Nokia’s autonomous networks architecture. You will work on the foundational platform capabilities that allow networks to sense, reason, act and learn while remaining secure, governable, auditable and aligned with telecom-grade operational requirements. You will help turn architectural concepts into working validation artifacts, prototypes, reference designs and technical decision points that enable Nokia to evaluate alternative approaches and converge toward winning solutions.

As part of our team, you will:

• Contribute to the architecture of Nokia’s autonomous networks platform across data management, agent runtime, model infrastructure, governance and security.
• Define architecture patterns for AI-native network operations, including multi-agent systems, domain agents, intent interpretation, reasoning workflows, action recommendation and closed-loop automation.
• Help shape data platform architecture for autonomous networks, including telemetry ingestion, semantic data products, event models, knowledge graphs, vector stores, time-series data, action/outcome history and cross-domain correlation.
• Contribute to agent runtime architecture, including agent orchestration, tool use, policy boundaries, A2A-style interactions, MCP-style integrations, workflow execution and runtime observability.
• Define model infrastructure requirements for LLMs, SLMs, RAG pipelines, domain-specific models, inference serving, model lifecycle management, evaluation and guardrail integration.
• Contribute to governance and security architecture, including identity, access control, policy enforcement, auditability, traceability, human-in-the-loop controls, blast-radius management and safe autonomous action.
• Build and guide working architectural validation artifacts, including prototypes, proof-of-concepts, reference implementations, demos, test harnesses and evaluation frameworks.
• Compare alternative technical approaches and communicate architectural trade-offs clearly to senior technical and business stakeholders.
• Work with product units, research teams, engineering teams and customer-facing organizations to translate strategic intent into implementable technical architecture.
• Contribute to architecture documentation, technical position papers, reusable patterns and internal guidance for autonomous network platform development.
• Track relevant ecosystem developments in agentic AI, cloud-native platforms, network automation, AI infrastructure, data platforms, security and telecom operations.
• Represent Nokia’s autonomous networks architecture in internal technical forums and, where needed, customer or ecosystem discussions.

You have deep experience in network architecture, cloud-native systems, automation, AI infrastructure or data platforms, and you are comfortable operating at the intersection of strategy, architecture and hands-on technical validation.

Must have:

• 15+ years of relevant experience in telecom, cloud, data center networking, network automation, AI infrastructure or large-scale distributed systems.
• Strong architecture experience in service provider, enterprise, cloud or mission-critical network environments.
• Good understanding of autonomous networks, network automation, SDN/NFV, telco cloud, cloud-native operations or AI-native operational systems.
• Experience defining architecture across multiple technical domains, such as data platforms, orchestration, AI/ML platforms, security, network control systems or operational support systems.
• Hands-on ability to build or guide prototypes, proof-of-concepts, reference implementations, validation environments or technical demos.
• Familiarity with cloud-native technologies such as Kubernetes, containers, Helm, GitOps, CI/CD, service meshes, observability stacks and infrastructure-as-code.
• Understanding of AI/ML infrastructure concepts such as LLMs, RAG, vector databases, model serving, fine-tuning, evaluation, prompt/tool orchestration and model lifecycle management.
• Familiarity with agentic AI concepts, including agents, tools, memory, planning, multi-agent collaboration, MCP-style integration, A2A-style interaction patterns and runtime governance.
• Strong understanding of network data, telemetry and models, including YANG, OpenConfig, gRPC, streaming telemetry, REST APIs, event streams and time-series data.
• Experience with data architectures involving Kafka or equivalent event systems, NoSQL databases, observability data stores, knowledge graphs, vector stores or semantic data layers.
• Knowledge of security and governance concepts relevant to AI-native operations, including identity, policy, audit, authorization, secure-by-design architecture and operational safety.

• Strong communication skills, with the ability to explain complex architecture choices, trade-offs and risks to senior technical and business stakeholders.

  Ability to operate across ambiguity, shape new technical domains and influence without relying only on formal authority.

Nice to have:

• Experience with telecom OSS/BSS, assurance, orchestration, inventory, service management, configuration management or closed-loop automation.
• Knowledge of RAN, Core, IP, optical, fixed access, transport, private wireless or edge networks.
• Experience with AI for network operations, root-cause analysis, service impact analysis, change impact analysis, action recommendation or intent-based automation.
• Experience with graph databases, semantic models, ontologies, digital twins or knowledge representation for operational systems.
• Experience building customer-facing proof-of-concepts or executive-level technology demonstrations.
• Prior exposure to hyperscaler AI platforms, open-source agent frameworks, model serving platforms, or enterprise AI governance systems.
• Participation in industry forums, standards, open-source communities or technical thought leadership.

What we offer

At Nokia, you will have the opportunity to shape the architecture of AI-native and autonomous networks at global scale. You will work with leading experts across telecom, cloud, AI, data, security and distributed systems, and contribute to technologies that will define how networks operate in the AI era.

This is a senior technical role for someone who wants to move beyond slideware architecture and help create working validation artifacts that influence real product and platform direction.

You will have the opportunity to:

• Work directly on Nokia’s autonomous networks architecture.
• Influence platform choices across data, agents, models, governance and security.
• Collaborate across CTO, research, product and engineering teams.
• Help define Nokia’s role in the AI Supercycle.
• Build proof points that turn architecture into executable technical direction.