Top Tech Jobs & Startup Jobs

Lead the technical vision and architecture for AWS cloud-native platforms and agentic AI systems. Establish scalable infrastructure, DevOps, GitOps, SRE, security, observability, data, and deployment standards. Govern architecture decisions, design distributed systems, create reference architectures and technical documentation, evaluate emerging technologies, advise product and partner teams, and mentor senior engineers. The role requires extensive AWS, Kubernetes, platform engineering, AI orchestration, distributed systems, and cloud security expertise.

Design, implement, and support Microsoft Intune and Autopilot endpoint management; migrate GPOs to compliance policies; deploy and manage applications; build automation with Azure tools; monitor device health and Microsoft 365 services; troubleshoot endpoint/security incidents; produce reports and documentation.

Provide administrative and paralegal support to litigation team: prepare and file court documents, draft and proofread pleadings, motions, discovery and settlement agreements, maintain organized case files, and coordinate case processing with attorneys and staff.

Lead architecture and evolution of enterprise-scale data, analytics, and MLOps platforms. Design AI-ready data foundations, semantic/ontology and federated catalog solutions, APIs and permission-aware discovery. Drive adoption through reference architectures, prototyping, R&D, and mentorship while ensuring security, governance, cost efficiency, and cloud-native operational excellence.

Manage a portfolio of Fintech clients, build executive relationships, prospect new business, align Experian data and fraud solutions to client objectives, negotiate contracts, and drive revenue growth and cross-functional delivery.

Lead strategy and roadmap for an enterprise developer platform and AI engineering capabilities. Define CI/CD, cloud, and security standards; drive AI-enabled developer tooling adoption; partner across engineering, security, and cloud teams; manage global senior leaders; own platform performance, budgets, vendor decisions, and continuous improvement.

Lead development of an internal AI platform enabling 5,000 developers to build, run, and govern agents. Own identity, rate limiting, data classification enforcement, audit logging, model access, agent marketplace, RAG and retrieval pipelines, and CI/CD AI integrations. Set architecture, governance, and roadmap; unblock teams and ship production AI systems at enterprise scale while leading a lean engineering organization.