Innova Solutions are seeking a seasoned, Senior Infrastructure Architect to define, govern, and evolve a large-scale infrastructure estate supporting more than 1,500 compute instances across distributed cloud, on-premises, and hybrid IT environments. The architect will provide end-to-end technical leadership across compute, storage, backup, networking, security, observability, automation, and resilience. The role requires deep expertise in multi-homed network design and enterprise security frameworks.

Demonstrable experience in AIOps to improve operational efficiency, service reliability, automate risk management and derive predictable business outcomes.

Required Qualifications

- 15+ years of progressive experience in infrastructure architecture, engineering, transformation and operations, including responsibility for complex enterprise environments.
- Proven experience architecting and governing estates of 1,500+ compute instances across data centers, public cloud, private cloud, edge and hybrid platforms.
- Expert-level knowledge of hypervisors, virtualization, container platforms, storage, backup and recovery, networking, identity, security, observability, and disaster recovery and business continuity.
- Strong hands-on architecture experience with at least two major public cloud platforms, preferably Microsoft Azure and AWS, including landing zones, connectivity, security controls, governance and cost management.
- Demonstrated expertise in multi-homed networking, routing, segmentation, firewalls, load balancing, DNS, SD-WAN, zero-trust design, and secure connectivity between cloud and on-premises environments.
- At least 3 years of experience with AI technologies, including 2+ years applying AIOps, machine learning, or intelligent automation in production infrastructure operations.
- Demonstrable experience modernizing NOC, SOC, TOC, or command-center operations through event correlation, anomaly detection, predictive analytics, automated remediation and operational copilots.
- Strong understanding of enterprise architecture principles, security frameworks, regulatory controls, risk management, and architecture governance.
- Experience leading architecture reviews, technical due diligence, platform standards, lifecycle roadmaps, and major transformation programs.
- Excellent executive communication, stakeholder management, facilitation and technical documentation skills.

Key Responsibilities
- Own the target-state architecture and multi-year modernization roadmap for enterprise infrastructure across data center, cloud,



edge and hybrid IT environments.
- Define reference architectures, guardrails, design patterns, and technology standards for compute, storage, backup, network, identity, security, monitoring, and automation.
- Review and approve high-level and low-level designs, exceptions, implementation plans, migration waves, and production-readiness criteria.
- Partner with security teams to embed zero-trust principles, privileged-access controls, segmentation, encryption, vulnerability management, and policy compliance into platform designs.
- Guide engineering and operations teams during major incidents, recurring problem investigations, capacity events, security events, and complex performance issues.
- Evaluate vendors and emerging technologies, conduct proofs of concept, support commercial evaluations, and present recommendations to senior leadership.

AI, AIOps, and Intelligent Automation Responsibilities
- Define the AI-enabled infrastructure operations strategy, use-case portfolio, reference architecture, governance model, and adoption roadmap.
- Design solutions for alert noise reduction, event correlation, anomaly detection, predictive capacity management, incident summarization, probable-cause analysis, and automated remediation.
- Integrate telemetry from infrastructure, applications, networks, security platforms, service management tools, and cloud-native services into unified operational intelligence workflows.
- Develop patterns for AI-assisted NOC, SOC, and TOC operations, including human-in-the-loop approvals, escalation controls, auditability, rollback, and measurable service outcomes.
- Apply generative AI and retrieval-augmented generation to operational knowledge, runbooks, architecture repositories, configuration data, and incident history while protecting sensitive information.
- Establish responsible AI controls covering data quality, privacy, security, access, explainability, model risk, hallucination management, monitoring, and regulatory compliance.
- Drive closed-loop automation using orchestration platforms, infrastructure-as-code, APIs, policy-as-code, and event-driven workflows.
- Define and monitor AI solution performance through accuracy,



precision, automation success rate, false-positive rate, time saved, avoided incidents, and business-value measures.
- Partner with data, AI, security, service management, and platform engineering teams to productionize models and operational agents safely.

Technical Competencies
- Cloud and platforms: Azure, AWS, cloud landing zones, virtualization, Kubernetes, containers, platform engineering, and hybrid-cloud management.
- Infrastructure: Windows and Linux, x86 compute, hyperconverged infrastructure, enterprise storage, data protection, backup, replication, and recovery.
- Networking: TCP/IP, BGP, OSPF, DNS, DHCP, IPAM, VPN, SD-WAN, load balancing, proxies, network segmentation, and cloud connectivity.
- Security: Zero trust, IAM, PAM, encryption, secrets management, vulnerability management, endpoint controls, secure configuration, and compliance frameworks.
- Automation: Terraform, Ansible, PowerShell, Python, CI/CD, Git-based workflows, APIs, orchestration, infrastructure-as-code, and policy-as-code.
- Observability and operations: Metrics, logs, traces, event management, discovery, CMDB, ITSM, service mapping, SRE practices, and operational analytics.
- AI and data: AIOps platforms, generative AI, machine learning concepts, vector search, retrieval-augmented generation, prompt design, model evaluation, and responsible AI controls.
- Architecture methods: Enterprise architecture frameworks, capability mapping, current-state and target-state design, roadmaps, dependency analysis, architecture decision records, and total-cost modeling.

Preferred Qualifications
- Bachelors or master’s degree in computer science, engineering, information systems, or a related discipline.
- Cloud architecture certifications such as Microsoft Certified: Azure Solutions Architect Expert or AWS Certified Solutions Architect – Qualified.
- Relevant certifications in enterprise architecture, networking, security, Kubernetes, service management, FinOps, or AI.
- Experience of AIOps based Operational insights or proactive event and incident management including event correlation, auto-ticketing and self-healing will be highly relevant.
- Experience in financial services or another highly regulated industry, with knowledge of audit, data protection, operational resilience, and third-party risk requirements.
- Experience supporting merger integration, data-center exits, large-scale migrations, platform rationalization, or global infrastructure transformation.

📌 Senior Infrastructure Architect (AI Enabled Hybrid Cloud) (Bengaluru)
🏢 Innova Solutions
📍 Bengaluru