Principal Network DevOps Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Principal Network DevOps Engineer based in India.

We are seeking a highly skilled engineering leader to transform enterprise network operations through advanced automation, cloud networking, and AI-driven technologies. In this role, you will design and implement intelligent platforms that combine network engineering, infrastructure-as-code, and agentic AI to improve operational efficiency, reliability, and scalability. You will lead strategic initiatives across global network infrastructure while developing autonomous workflows, AI-powered troubleshooting capabilities, and enterprise-wide integration solutions. Working closely with cloud, security, platform, architecture, and operations teams, you will establish engineering standards and drive the adoption of secure, scalable automation practices. You will also help shape the future of network operations by leveraging generative AI, large language models, and intelligent knowledge systems. This is an opportunity to influence technical strategy, solve complex infrastructure challenges, and deliver measurable improvements across a global technology environment.

• Agentic AI & Intelligent Automation: Design, develop, and deploy AI-powered operational platforms that modernize network and cloud infrastructure management. Build intelligent assistants, decision-support systems, and autonomous or semi-autonomous workflows capable of multi-step reasoning and execution. Implement AI-driven troubleshooting, incident triage, root cause analysis, diagnostics, and operational insights to reduce manual effort and improve service reliability.
• Generative AI & Knowledge Retrieval: Develop enterprise AI capabilities using large language models (LLMs), Retrieval-Augmented Generation (RAG), and context-aware knowledge retrieval systems. Integrate information from documentation, operational records, runbooks, policies, and enterprise applications to improve search, summarization, recommendations, and technical decision-making.
• Network & Cloud Platform Engineering: Lead the design, deployment, operation, and optimization of global network infrastructure and cloud connectivity platforms. Define technical architecture, roadmaps, and network standards while ensuring infrastructure deployments meet security, reliability, scalability, and performance requirements. Contribute to strategic backbone networking initiatives and manage enterprise-scale Secure Access Service Edge (SASE) solutions.
• Network Automation & Infrastructure-as-Code: Develop scalable automation frameworks using Python, APIs, Terraform, AWS CloudFormation, and related technologies. Build reusable automation services, integration components, software development kits, and orchestration capabilities. Automate network provisioning, configuration validation, compliance assessments, governance enforcement, and remediation workflows.
• DevOps, GitOps & CI/CD: Implement modern engineering practices across network platforms and automation services, including GitOps, continuous integration, and continuous delivery pipelines. Establish reusable design patterns, coding standards, and infrastructure-as-code best practices while enabling self-service automation for engineering and operations teams.
• Cloud & Enterprise Integrations: Design and implement secure integrations between cloud platforms, enterprise applications, security tools, IT service management systems, monitoring platforms, and knowledge repositories. Develop API-first, event-driven integration frameworks and workflow orchestration services that support reliable data exchange across distributed systems.
• Security, Governance & Risk Automation: Build automated controls for governance, risk management, compliance, and audit requirements. Implement intelligent approval workflows, policy enforcement, traceability, audit trails, and accountability mechanisms. Ensure AI-driven solutions comply with enterprise security, privacy, and regulatory requirements, incorporating human approval for sensitive or high-risk operational actions.
• Observability & Operational Intelligence: Develop comprehensive observability and telemetry platforms using metrics, logs, traces, and events. Create dashboards, alerts, health monitoring, and performance reporting capabilities. Implement anomaly detection, predictive analytics, and AI-driven insights to enable proactive issue detection, improve operational visibility, and optimize infrastructure performance.
• Technical Strategy & Architecture Leadership: Define the technical vision and architecture for network automation, cloud connectivity, and AI-enabled operational platforms. Lead large-scale infrastructure initiatives, document technical designs and policies, influence engineering decisions across multiple teams, and ensure alignment with enterprise architecture standards.
• Cross-Functional Collaboration & Delivery: Partner with engineering, security, architecture, cloud, platform, operations, and business teams to deliver scalable and resilient solutions. Participate in Agile delivery processes, manage long-term initiatives and project milestones, communicate technical recommendations to stakeholders, and support enterprise-wide adoption of AI-driven operational capabilities.
• Continuous Innovation: Evaluate emerging AI technologies, automation frameworks, and cloud networking capabilities. Identify opportunities to improve engineering productivity, operational resilience, and service quality while establishing responsible AI practices and scalable implementation standards.

Requirements:

• Education & Professional Experience: Bachelor's degree in Computer Science or a related discipline, or equivalent practical experience. At least 7 years of experience in software engineering, platform engineering, automation engineering, cloud engineering, infrastructure engineering, network engineering, or a related technical field.
• Software Development & Automation: Strong expertise in Python development, API engineering, automation frameworks, software design principles, and enterprise-scale automation solutions. Ability to develop maintainable, reusable, and production-ready software components for complex infrastructure environments.
• Infrastructure-as-Code & DevOps: Hands-on experience with Terraform, AWS CloudFormation, or comparable infrastructure-as-code technologies. Strong understanding of Git, GitOps, CI/CD pipelines, modern automation platforms, and Agile software delivery practices.
• Cloud Platforms & Networking: Experience with at least one major cloud platform, including AWS, Microsoft Azure, or Google Cloud Platform, along with a solid understanding of cloud networking and hybrid connectivity. Demonstrated AWS experience with services such as Transit Gateway, Direct Connect, Lambda, Route 53, VPC, and Cloud WAN is particularly valuable.
• Network Engineering & Security: Strong knowledge of enterprise networking, network architecture, firewalls, security configurations, cloud connectivity, and troubleshooting. Ability to design, deploy, and optimize secure network infrastructure that meets enterprise-scale performance and availability requirements.
• Enterprise Integrations: Experience building integrations across enterprise applications, cloud services, APIs, operational tools, and IT service management platforms. Understanding of event-driven architectures, API-first design, distributed systems, and secure data exchange patterns.
• Agentic AI & Generative AI: Experience designing or implementing agentic AI solutions, intelligent automation platforms, generative AI applications, or LLM-powered systems is preferred. Familiarity with AI assistants, multi-step workflow orchestration, intelligent decision-support tools, and AI-enabled operational processes is highly desirable.
• RAG & Enterprise Knowledge Systems: Understanding of Retrieval-Augmented Generation, enterprise search, knowledge ingestion, information retrieval, and knowledge integration patterns. Experience building systems that retrieve and contextualize information from multiple enterprise sources is an advantage.
• AI Governance & Responsible AI: Familiarity with AI security, governance, privacy, compliance, auditability, explainability, and responsible AI practices. Ability to implement monitoring, evaluation, human-in-the-loop approval processes, and lifecycle management controls for AI-powered operational systems.
• Observability & Analytics: Experience with monitoring platforms, telemetry pipelines, operational reporting, anomaly detection, predictive analytics, or intelligent troubleshooting solutions. Ability to transform infrastructure data into actionable insights that improve operational decision-making.
• Technical Leadership & Strategic Thinking: Demonstrated experience leading large-scale infrastructure or automation initiatives and influencing technical strategy across multiple teams. Strong system design, analytical reasoning, troubleshooting, and problem-solving skills, with the ability to balance technical innovation, security, and operational requirements.
• Communication & Stakeholder Management: Excellent written and verbal communication skills, including the ability to present technical proposals, architecture diagrams, policies, and design decisions to diverse audiences. Strong collaboration skills and the ability to coordinate long-term, milestone-driven initiatives across cross-functional teams.
• Preferred Certifications: Cisco Certified Network Associate (CCNA) or Cisco Certified Network Professional (CCNP) certifications are advantageous.
• Additional Preferred Experience: Exposure to conversational AI, self-service automation platforms, AI-powered operational intelligence, workflow orchestration, enterprise AI adoption initiatives, and integrations between AI systems and monitoring, ITSM, or enterprise applications is beneficial.

Benefits:

• Competitive Compensation: A competitive compensation package based on experience, technical expertise, and geographic location.
• Performance-Based Rewards: Potential eligibility for annual cash bonuses and other incentive compensation, depending on the role and applicable compensation arrangements.
• Equity Opportunities: Stock grants may be included as part of the overall compensation package, subject to eligibility.
• Remote Work Flexibility: An India-based remote working arrangement, with Bengaluru also listed as a work location.
• Comprehensive Benefits: Access to a benefits package, with specific healthcare coverage and other provisions to be confirmed during recruitment.
• Career Development: Opportunities to deepen expertise in cloud networking, DevOps, infrastructure automation, generative AI, and agentic AI technologies.
• Technical Ownership: The opportunity to influence global network architecture, establish engineering standards, and lead high-impact infrastructure initiatives.
• Innovation & Learning: Exposure to emerging AI technologies, enterprise-scale cloud platforms, and advanced operational automation solutions.
• Collaborative Environment: Work alongside multidisciplinary engineering, security, cloud, architecture, and operations teams on complex technical challenges.
• Meaningful Impact: Help build secure, reliable, and intelligent infrastructure platforms that improve operational efficiency and support innovative digital products.