Generative AI Architect

Job Summary

This Architect role focuses on delivering complex AI deployment architecture projects within a hybrid work model for a global organization. The professional will manage end to end project execution coordinate cross functional teams and ensure high quality AI solutions are deployed reliably into production environments. Experience in telecom billing and revenue management is beneficial.

Responsibilities

Manage large scale AI deployment architecture projects from initiation through closure ensuring that project scope schedule and quality objectives are consistently achieved within agreed constraints

Coordinate cross functional teams of engineers architects analysts and stakeholders to ensure AI solutions are designed built and deployed in alignment with enterprise architectural guidelines and business expectations

Monitor project plans milestones and dependencies using structured project management practices to ensure timely delivery of AI deployment initiatives in a hybrid work environment

Drive detailed project planning for AI infrastructure environments and integration workflows to ensure robust secure and scalable deployments that support long term business growth

Track project risks issues and assumptions related to AI deployment architecture and implement effective mitigation actions that reduce business impact and improve delivery predictability

Collaborate with product owners data scientists and platform engineers to translate AI solution requirements into executable deployment plans that are technically feasible and operationally sustainable

Oversee project governance forums and status reporting providing clear and concise progress updates resource needs and risk insights to senior stakeholders and steering committees

Ensure alignment of AI deployment architecture projects with organizational standards for security compliance and data privacy thereby protecting customer trust and regulatory adherence

Optimize project resource utilization across hybrid teams by balancing workloads clarifying priorities and enabling efficient collaboration across time zones where needed

Drive continuous improvement by capturing lessons learned from AI deployment projects and translating these insights into refined delivery processes and reusable best practices

Partner with operations and support teams to ensure AI solutions are handed over with well defined runbooks monitoring strategies and incident response procedures for stable production operations

Engage with telecom billing and revenue management stakeholders where applicable to ensure AI deployment outcomes support accurate charging rating and revenue assurance processes

Measure project outcomes using agreed key performance indicators such as deployment reliability time to market and stakeholder satisfaction to demonstrate tangible business value from AI initiatives

Qualifications

Require extensive experience in managing complex technology projects involving AI deployment architecture with a proven track record of delivering production ready solutions in enterprise environments

Require strong understanding of cloud based infrastructure containerization orchestration and continuous integration and continuous delivery practices to support automated and repeatable AI deployments

Require ability to interpret solution designs data flows and integration patterns so that project plans accurately reflect the technical realities of AI platforms and related systems

Require excellent communication and stakeholder management skills to facilitate collaboration between technical and non technical teams and to manage expectations in a hybrid work model

Require prior exposure to enterprise governance processes including risk management change control and compliance review for technology programs with significant business impact

Nice to have experience in telecom billing and revenue management domains including understanding of rating charging invoicing and revenue assurance processes that may interface with AI solutions

Nice to have familiarity with data governance model lifecycle management and monitoring practices that ensure AI deployments remain ethical explainable and aligned with organizational values

Nice to have experience working with distributed or hybrid teams and using collaboration tools that support effective planning tracking and communication in complex technology programs