AI Orchestrator

Accountabilities:: Orchestrate end-to-end delivery , mapping and governing the value stream across the complete SDLC from upstream demand through technical execution and delivery. Coordinate workflows involving people and AI agents across the delivery pipeline, ensuring effective collaboration and continuity between stages. Govern delivery performance to maintain appropriate levels of time, cost, quality, and compliance throughout the value stream. Define, review, and continuously evolve delivery processes, standards, governance practices, and team rituals. Monitor and maintain workflow health , identifying bottlenecks, dependencies, exceptions, risks, and opportunities for improvement. Act as the bridge between upstream business or product demand and the technical execution performed by AI Engineers and AI Deployment Engineers. Translate requirements into actionable workflows while assessing the technical and financial feasibility of proposed solutions. Define and monitor success metrics such as ROI, accuracy rates, delivery performance, and other relevant value indicators . Prioritize initiatives and delivery activities based on the value they generate for the organization and end users. Govern AI-enabled workflows by managing dependencies, exception paths, levels of agent autonomy, and appropriate boundaries for human approval. Promote consistency across the delivery model while identifying opportunities to improve efficiency, quality, and scalability. Develop AI fluency across the team through continuous learning, enablement, and practical adoption of AI-driven ways of working. Support the squad in transitioning toward a model where teams effectively orchestrate AI agents and workflows rather than relying primarily on accumulating specialized capabilities. Facilitate continuous improvement of the overall delivery operating model and encourage experimentation with new AI-enabled practices. Requirements: Strong experience in end-to-end delivery orchestration , program/project management, product delivery, operations, transformation, or a comparable cross-functional discipline. Ability to understand and govern the full SDLC and Value Stream , connecting upstream requirements with downstream technical execution. Strong systems thinking and the ability to understand complex workflows, dependencies, bottlenecks, exceptions, and interactions across multiple teams and technologies. Experience establishing or improving processes, standards, governance models, and delivery rituals . Strong analytical and decision-making skills, with the ability to balance cost, time, quality, technical feasibility, compliance, and business value . Experience defining and tracking delivery or business success metrics, including ROI, quality/accuracy indicators, efficiency, or comparable performance measures. Strong stakeholder management and communication skills, with the ability to coordinate multidisciplinary teams without relying exclusively on formal authority. Demonstrated AI fluency and an understanding of how AI agents can participate in workflows and software delivery processes. Ability to govern AI-enabled workflows, including dependencies, exceptions, autonomy levels, escalation paths, and human approval boundaries. Strong adaptability and continuous-improvement mindset, with an interest in evolving traditional ways of working through AI-enabled approaches. Ability to translate complex business and technical requirements into clear workflows, priorities, and execution plans. Strong facilitation, coordination, and organizational skills to maintain alignment across people, agents, and delivery stages. Willingness and ability to continuously develop AI capabilities and help teams adopt new AI-driven operating models. Benefits: Fully remote work arrangement in Brazil. Opportunities to work with AI-driven delivery models and emerging technologies. Exposure to end-to-end transformation initiatives spanning business, technology, and software delivery. Continuous learning and development opportunities. Collaborative work with multidisciplinary teams and AI-focused engineering professionals. Opportunity to contribute to the evolution of modern AI-native ways of working. Professional growth through involvement in complex, cross-functional, and international technology initiatives.