AI summary
Lead the technical delivery of enterprise-wide AI and AIOps initiatives, overseeing complex projects, operational delivery, and cross-functional team collaboration.
Eligible from: US only
Job Description
- Orchestrate Agentic AI & AIOps Delivery: Serve as the technical delivery orchestrator for enterprise-wide Agentic AIOps initiatives. Drive milestone tracking, integration of developed code blocks, and deployment of multi-agent reasoning systems, dynamic agent registries, and tool-calling interfaces utilizing Google Cloud Vertex AI, Model Context Protocol (MCP), and agentic frameworks.
- Lead Observability & Self-Healing Automation: Direct operational delivery for enterprise observability programs. Oversee telemetry ingestion, monitoring standardization, automated alerting, and self-healing automation workflows across multi-cloud infrastructure using enterprise observability tools (e.g., Dynatrace, Splunk, CloudWatch).
- Vulnerability Tracking & Security Remediation: Formulate, integrate, and deploy standardized vulnerability tracking workflows and automated remediation frameworks across application and infrastructure portfolios to maintain strict enterprise compliance and security posture.
- Cross-Functional Team Orchestration: Harmonize diverse engineering, application support, data, and security teams. Manage resource dependencies, navigate competing priorities, and drive strict accountability across separate technical units to meet consolidated timeline goals.
- Monthly Project Reporting & Savings Tracking: Establish quantitative KPIs to track delivery health, token consumption, operational MTTR improvements, and financial value. Build and maintain executive reporting frameworks that explicitly measure and report cost savings generated by AI and automation initiatives.
- Executive Communication & Autonomy: Establish concise, high-level reporting cadences for executive leadership. Anticipate bottlenecks, clear technical roadblocks independently, and distill complex, multi-team technical statuses into clear, actionable executive updates.
Requirements
- Master’s degree preferred; Bachelor’s degree in Computer Science, Information Technology, Systems Engineering, or a related field required.
- 8+ years leading complex technical projects, product delivery, or cloud infrastructure rollouts within a global enterprise IT environment, with at least 2+ years leading AI/AIOps platform deployments.
- Mastery of AI concepts, including Large Language Models (LLMs), Agentic AI, multi-agent reasoning, tool-calling architectures, Retrieval-Augmented Generation (RAG), and the Model Context Protocol (MCP).
- Hands-on experience with enterprise monitoring platforms (e.g., Dynatrace, Splunk, CloudWatch), cloud environments (GCP, AWS), and CI/CD pipeline automation.
- Proven ability to translate complex I&O environments into contextual schemas for AI consumption, paired with experience establishing guardrails for data security, AI safety, and compliance.
- Deep familiarity with Site Reliability Engineering (SRE) principles, automated testing, IaC, and data pipeline oversight (e.g., Snowflake/ETL validation).
About the job
- Posted on
- Aug 24, 2026
- Job type
- Full-time
- Location
- Remote, usRemote
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