Network Automation & AI Consultant

Job description

Who We Are At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. The Role About the role At Kyndryl, we are looking for a Network Platforms, Automation & AI Operations consultant to help shape, industrialize, and deliver the next generation of enterprise network modernization capabilities. This role is both a client-facing transformation role and a capability-building / software-building role. The successful candidate will help Kyndryl design, build, and scale modernization programs that combine network architecture, software engineering, cloud-native platforms, automation, observability, data engineering, AIOps, and AI-enabled operations. You will work with large-scale enterprise environments, helping customers evolve from traditional network operations to more software-driven, observable, automated, data-informed, and resilient operating models. This includes defining architectures, roadmaps, reusable assets, delivery accelerators, and platform capabilities that improve reliability, reduce operational effort, accelerate incident resolution, and increase service quality. A key part of the role will be to design and develop reusable software components for network modernization, including automation services, API integrations, data ingestion pipelines, observability connectors, AI-enabled operational workflows, copilots, agentic AI components, and reusable accelerators that can be industrialized across multiple clients and engagements. The role requires a strong foundation in enterprise networking, but it is equally important that the candidate brings a strong engineering mindset and hands-on experience across software development, APIs, automation, data pipelines, cloud platforms, Kubernetes/container platforms, DevOps practices, agile delivery, and AI-enabled operational use cases. You will act as a trusted advisor to client stakeholders while also building reusable capabilities for Kyndryl, including assessment frameworks, reference architectures, automation blueprints, observability models, data/AI integration patterns, agentic AI use cases, demos, playbooks, reusable code components, and delivery methodologies. Responsibilities Network Platforms & Enterprise Architecture Design and deliver modern enterprise network architectures across data center, campus, WAN, cloud, and edge environments. Translate business, application, and operational requirements into scalable, secure, observable, and automated network platform designs. Support the modernization of traditional network environments through software-defined networking, cloud networking, segmentation, resilience, and platform-based operating models. Integrate network platforms with cloud services, security platforms, ITSM tools, observability solutions, and automation/orchestration frameworks. Provide technical leadership in complex client environments, ensuring that network modernization initiatives are aligned with business outcomes, operational requirements, and long-term scalability. Software Engineering, Automation & Cloud-Native Platforms Design and develop reusable software components to support network modernization and AI-enabled operations. Build automation services, APIs, connectors, workflows, and integration components using modern software engineering practices. Develop Infrastructure as Code and automation frameworks for network lifecycle management, configuration, compliance, validation, and remediation. Contribute to cloud-native platform designs using containers, Kubernetes, CI/CD pipelines, Git-based workflows, and DevOps practices. Industrialize reusable assets, code libraries, templates, and delivery accelerators that can be applied across multiple clients and engagements. Observability, Data Engineering & AIOps Define observability frameworks for network operations, including telemetry, metrics, logs, events, flows, traces, correlation, and service-level indicators. Design and implement data ingestion, processing, and analytics pipelines to make network operational data usable for automation, analytics, and AI-enabled use cases. Integrate observability and AIOps platforms with network, cloud, security, and IT operations ecosystems. Develop use cases for anomaly detection, incident correlation, capacity forecasting, root cause analysis, service impact analysis, and operational decision support. Help customers evolve from reactive monitoring to more predictive, data-driven, and automated operational models. AI Agents & Intelligent Operations Design and develop AI-enabled operational workflows, copilots, and agentic components for NetOps and NOC environments. Build or integrate agents capable of supporting tasks such as event triage, knowledge retrieval, incident enrichment, recommended remediation, change validation, and operational reporting. Define integration patterns between AI agents, observability platforms, automation tools, ITSM systems, knowledge bases, and network control interfaces. Support the responsible use of AI in network operations, including governance, human-in-the-loop controls, auditability, security, and operational risk management. Translate AI opportunities into practical, measurable, and production-oriented use cases for enterprise network operations. Consulting, Delivery & Capability Building Lead or contribute to client assessments, technical workshops, architecture reviews, and transformation roadmaps. Support advisory, pre-sales, and solutioning activities, including technical proposals, solution narratives, effort estimation, and value articulation. Act as a trusted advisor to client stakeholders across network, infrastructure, operations, cloud, security, and application teams. Create reusable Kyndryl capabilities, including assessment frameworks, reference architectures, blueprints, demos, playbooks, delivery methodologies, and reusable software assets. Mentor and collaborate with engineers, architects, developers, data specialists, and operations teams to build a multidisciplinary delivery capability. Who You Are Job Qualifications Mandatory Degree in Telecommunications Engineering, Computer Science, Software Engineering, Data Engineering, or equivalent professional experience. Strong experience in enterprise networking, network platforms, or network operations across complex environments such as data center, campus, WAN, cloud, or edge. Solid understanding of network architecture principles, including routing, switching, segmentation, resilience, security, hybrid connectivity, and operational models. Hands-on experience in software development and automation using technologies such as Python, APIs, Git, CI/CD pipelines, Ansible, Terraform, or similar tools. Experience designing or building reusable software components, automation workflows, integrations, connectors, scripts, services, or platform accelerators. Practical knowledge of cloud platforms and cloud-native technologies, including at least one major public cloud provider and exposure to containers, Kubernetes, or platform engineering practices. Understanding of observability and operations data, including telemetry, metrics, logs, events, monitoring, correlation, analytics, and service reliability concepts. Exposure to data engineering or analytics applied to IT/network operations, including data ingestion, transformation, dashboards, reporting, or AI-ready data pipelines. Understanding of AI-enabled operations, AIOps, or applied AI use cases such as anomaly detection, incident correlation, knowledge r