AI Network Automation Engineer

We are seeking a highly skilled Senior AI Platform & Agentic Automation Engineer to lead the transformation of traditional operational processes into intelligent, AI-driven, autonomous, and self-improving platforms. This role will be responsible for designing, developing, integrating, and operationalizing AI-powered solutions that leverage Generative AI, Large Language Models (LLMs), enterprise knowledge systems, intelligent workflow orchestration, advanced analytics, and automation technologies to modernize operational workflows and engineering productivity. The ideal candidate combines deep expertise in software engineering, cloud platforms, enterprise integrations, Infrastructure-as-Code (IaC), automation frameworks, observability, operational analytics, and AI technologies with hands-on experience building intelligent operational systems that drive measurable business outcomes. The successful candidate will play a key role in building AI-powered assistant capabilities, intelligent operational workflows, decision-support systems, enterprise knowledge solutions, and autonomous automation platforms that improve operational efficiency, governance, compliance, and service quality. The engineer will partner closely with Engineering, Security, Architecture, Cloud, Platform, Operations, and Business teams to build scalable, secure, resilient, and intelligent AI-powered platforms while driving enterprise adoption of Agentic AI capabilities., Agentic AI & Intelligent Automation

• Design and implement AI-driven operational platforms and intelligent automation solutions.
• Build AI-powered assistants, decision-support systems, and operational intelligence capabilities.
• Design autonomous and semi-autonomous workflow orchestration solutions.
• Develop multi-step reasoning and intelligent workflow execution capabilities.
• Build AI-powered troubleshooting, diagnostics, incident triage, root cause analysis, and operational insight solutions.
• Implement enterprise knowledge retrieval and retrieval-augmented generation (RAG) capabilities.
• Design context-aware AI systems that retrieve, correlate, analyze, and act on data from multiple enterprise sources.
• Develop conversational and self-service experiences using modern collaboration and communication platforms.
• Design human-in-the-loop approval workflows for operational, governance, security, and risk-sensitive activities.
• Implement AI observability, evaluation, monitoring, governance, auditability, and lifecycle management capabilities.
• Establish responsible AI, security, compliance, and governance standards.
• Evaluate emerging AI technologies and identify opportunities to improve operational effectiveness and engineering productivity.
• Drive enterprise adoption of AI-enabled operational and business capabilities.

Platform Engineering & Automation

• Design and develop scalable automation frameworks using Python, APIs, Infrastructure-as-Code (IaC), and modern automation technologies.
• Build reusable automation services, integration components, SDKs, and orchestration capabilities.
• Implement GitOps and CI/CD workflows across enterprise platforms and automation services.
• Automate provisioning, validation, compliance assessment, governance controls, and remediation workflows.
• Develop self-service automation platforms for engineering and operational teams.
• Establish automation standards, architecture patterns, and engineering best practices.
• Drive automation-first operating models across enterprise technology platforms.

Cloud & Enterprise Integrations

• Design and develop integrations across enterprise systems, cloud platforms, operational tools, security platforms, and knowledge repositories.
• Build scalable enterprise connector and API integration frameworks.
• Design secure data exchange and workflow orchestration services across distributed systems.
• Develop event-driven and API-first integration architectures.
• Automate enterprise workflow execution across multiple technology domains.
• Collaborate with platform and cloud engineering teams to build scalable, resilient, and secure solutions.

Knowledge Management & AI Enablement

• Build enterprise knowledge platforms leveraging structured and unstructured information sources.
• Develop knowledge retrieval, search, summarization, and recommendation capabilities.
• Design knowledge ingestion, enrichment, classification, and content management workflows.
• Enable AI-powered access to enterprise documentation, runbooks, policies, standards, operational records, and knowledge repositories.
• Improve knowledge discoverability and operational decision-making through intelligent knowledge systems.

Security, Risk & Governance Automation

• Build automation capabilities supporting governance, risk, compliance, and audit requirements.
• Develop intelligent approval workflows and policy enforcement capabilities.
• Design AI solutions that comply with enterprise security, privacy, and regulatory requirements.
• Implement audit trails, traceability, explainability, and operational accountability controls.
• Integrate security and governance controls throughout AI and automation workflows.
• Collaborate with security and compliance teams to establish enterprise AI governance standards.

Observability, Analytics & Operational Intelligence

• Build observability, telemetry, monitoring, reporting, and operational intelligence platforms.
• Develop analytics and insight solutions that support operational decision-making.
• Create dashboards, alerts, health monitoring, and performance measurement capabilities.
• Implement anomaly detection, predictive analytics, and operational reporting solutions.
• Improve operational visibility through metrics, logs, traces, events, and AI-driven insights.
• Enable proactive operational management through intelligent analytics.

10+ years of experience in Automation Engineering, Platform Engineering, Cloud Technologies, Enterprise Systems Integration, Infrastructure Automation, Intelligent Automation, and AI-Driven Operations. Strong experience in Artificial Intelligence (AI), Agentic AI Systems, Generative AI, Large Language Models (LLMs), Intelligent Automation, Autonomous Workflow Orchestration, Enterprise Knowledge Platforms, Retrieval-Augmented Generation (RAG), Decision-Support Systems, Operational Analytics, and AI-Driven Operations. Experience designing and implementing intelligent automation platforms that improve operational efficiency, automate complex workflows, reduce manual effort, accelerate issue resolution, enhance operational visibility, and enable AI-powered business and operational outcomes., * 10+ years of experience in software engineering, platform engineering, automation engineering, cloud engineering, infrastructure engineering, or related technical disciplines.

• Strong expertise in Python development, API development, automation engineering, and software design.
• Hands-on experience with Infrastructure-as-Code (IaC), CI/CD, GitOps, and enterprise automation platforms.
• Experience designing and implementing large-scale enterprise automation solutions.
• Experience developing integrations across enterprise applications, cloud services, APIs, and operational platforms.
• Strong understanding of cloud platforms including AWS, Azure, and/or GCP.
• Strong analytical, troubleshooting, problem-solving, and system design skills.
• Experience designing secure, scalable, resilient, and highly available enterprise platforms.
• Excellent communication, collaboration, and stakeholder engagement skills.

Preferred Qualifications

• Experience designing and implementing Agentic AI solutions and intelligent automation platforms.
• Experience with Generative AI technologies and Large Language Models (LLMs).
• Experience developing AI-powered assistants, workflow automation solutions, or intelligent operational platforms.
• Understanding of Retrieval-Augmented Generation (RAG), enterprise search, and knowledge integration patterns.
• Experience integrating AI solutions with APIs, operational platforms, monitoring systems, ITSM tools, and enterprise applications.
• Familiarity with AI governance, security, compliance, auditability, explainability, and responsible AI practices.
• Experience building conversational experiences and self-service automation platforms.
• Experience developing operational analytics, decision-support, workflow orchestration, or operational intelligence solutions.
• Experience supporting enterprise-scale AI adoption initiatives.