In your career, let’s prove what’s possible.
- Design and implement enterprise observability strategies across cloud, infrastructure, applications, and platforms.
- Build telemetry pipelines that ingest logs, metrics, traces, events, and topology information.
- Deploy and tune observability platforms to improve operational visibility and service reliability.
- Develop AIOps capabilities including anomaly detection, event correlation, noise reduction, and predictive insights.
- Partner with SRE, platform engineering, cybersecurity, and service operations teams to identify key operational signals.
- Create dashboards, service maps, operational scorecards, and SLO-driven reporting.
- Integrate observability data into AI agents, automation workflows, and operational platforms.
- Establish telemetry standards and observability engineering best practices.
- Drive continuous improvements in MTTD, MTTR, and service health monitoring.
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In your career, let’s prove what’s possible.
- Own the cloud platform reference architecture and roadmaps across AWS and Azure; align with enterprise architecture, security, data, and app teams.
- Define and maintain golden paths (IaC modules, pipeline templates, reference stacks) for common workloads (containers, serverless, data, analytics, batch).
- Establish multi-cloud landing zones (AWS Organizations + Control Tower; Azure Management Groups + Landing Zones) with policy, identity, and network guardrails.
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In your career, let’s prove what’s possible.
- Define the enterprise architecture and technology strategy for Agentic AI, AIOps, autonomous operations, and intelligent automation.
- Establish architectural standards, design patterns, and governance frameworks for AI agents and multi-agent systems.
- Design the integration architecture connecting agents to enterprise systems including ServiceNow, cloud platforms, observability platforms, CMDB, developer platforms, and security tooling.
- Develop reference architectures for AI-powered incident response, service management, platform operations, FinOps, cybersecurity, and disaster recovery.
- Partner with executives and technology leaders to align agentic capabilities with business and operational priorities.
- Evaluate emerging technologies, frameworks, and vendors in AI, automation, platform engineering, and cloud-native ecosystems.
- Define policies, controls, and approval models that enable safe autonomous operations.
- Drive architecture reviews and technical governance across multiple engineering and operations teams.
- Mentor engineers and architects while fostering innovation and best practices.
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In your career, let’s prove what’s possible.
- Lead the design and implementation of Lam's Agent Platform and Internal Developer Platform.
- Build and operate the cloud-native infrastructure supporting AI agents and automation services.
- Establish platform engineering standards, reusable templates, golden paths, and self-service capabilities.
- Implement GitOps, Infrastructure as Code, policy-as-code, and secure software delivery practices.
- Design deployment pipelines, observability standards, operational controls, and runtime governance.
- Partner with architects, SRE teams, and application teams to onboard services onto the platform.
- Define scalability, reliability, and resiliency requirements for enterprise automation workloads.
- Drive adoption of cloud-native engineering practices across the organization.
- Mentor engineers and build platform engineering excellence.
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