openleverjobgether
Technical Delivery Lead
Jobgether
LocationUS
EmploymentFull-time
Posted2026-08-25T08:39:53.990000+00:00
Last observed2026-08-26 21:51:40.410433
Job idjobgether-jobgether:lever:deffa54b-fe05-4bd0-a8bd-710baf3fbcb0
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Technical Delivery Lead based in the United States. This role leads the delivery of complex enterprise technology initiatives at the intersection of Agentic AI, AIOps, cloud infrastructure, observability, and security. You will orchestrate multi-team delivery, integrating AI capabilities and automation into large-scale technology environments. The position combines technical leadership with strong program execution, requiring you to translate sophisticated engineering work into measurable business outcomes. You will oversee initiatives spanning multi-agent systems, observability, self-healing automation, vulnerability remediation, and cloud operations. Success will depend on your ability to coordinate engineering, application support, data, and security teams while managing dependencies and competing priorities. You will also establish executive reporting around delivery health, operational improvements, AI usage, and financial value. This is an impactful opportunity for a technically sophisticated delivery leader who thrives in global enterprise environments and can independently turn complex initiatives into successful outcomes. Agentic AI & AIOps delivery: Orchestrate enterprise-wide Agentic AI and AIOps initiatives, tracking milestones, integrating developed code, and coordinating deployment of multi-agent reasoning systems, dynamic agent registries, and tool-calling interfaces. AI platform integration: Support delivery involving Google Cloud Vertex AI, Model Context Protocol (MCP), agentic frameworks, and related AI technologies while ensuring initiatives remain aligned with technical and business objectives. Observability and self-healing: Lead operational delivery for enterprise observability programs, overseeing telemetry ingestion, monitoring standardization, automated alerting, and self-healing workflows across multi-cloud environments. Security remediation: Drive standardized vulnerability tracking and automated remediation frameworks across application and infrastructure portfolios to strengthen enterprise security and compliance. Cross-functional orchestration: Coordinate engineering, application support, data, security, and other technical teams, managing dependencies, resources, competing priorities, and accountability against consolidated delivery timelines. Performance and value tracking: Establish quantitative KPIs covering delivery health, token consumption, operational improvements, MTTR, automation outcomes, and financial savings. Executive reporting: Build and maintain concise reporting frameworks that communicate delivery status, risks, operational improvements, and measurable business value to executive leadership. Technical problem solving: Anticipate bottlenecks, remove technical roadblocks, and independently drive resolution across complex, multi-team initiatives. Stakeholder communication: Translate sophisticated technical information into clear, actionable updates for both technical stakeholders and senior executives. Requirements: Education: Bachelor’s degree in Computer Science, Information Technology, Systems Engineering, or a related technical discipline is required; a Master’s degree is preferred. Experience: 8+ years leading complex technical projects, product delivery initiatives, or cloud infrastructure rollouts within global enterprise IT environments, including at least 2+ years leading AI or AIOps platform deployments. AI expertise: Strong understanding of Large Language Models (LLMs), Agentic AI, multi-agent reasoning, tool-calling architectures, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP). Cloud and monitoring: Hands-on experience with enterprise monitoring platforms such as Dynatrace, Splunk, or CloudWatch, as well as cloud environments including GCP and AWS. Automation: Experience with CI/CD pipeline automation, Infrastructure as
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