Senior Manager, AI CoE
Senior Engineering Manager – AI CoE
About Redwood
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Redwood Software helps the world's largest enterprises automate mission-critical business processes. Our platforms support complex enterprise workloads across ERP systems, business applications, cloud infrastructure, and on-premises environments.
Redwood is building reusable AI infrastructure, agentic capabilities, developer tools, and platform services that enable enterprise-ready AI features across its product portfolio.
Role Mission
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As a Senior Engineering Manager, you will lead the engineering team responsible for delivering Redwood's shared AI platform and agentic capabilities.
You will translate the AI strategy into an executable engineering roadmap, build a high-performing team, and ensure the delivery of secure, scalable, observable, and commercially valuable AI systems. The role requires sufficient technical depth to guide architecture and challenge engineering decisions while remaining accountable for people's leadership, execution, team health, and delivery outcomes.
Key Responsibilities
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- Lead one or more engineering teams responsible for AI platform services, agentic capabilities, developer tools, and product integrations.
- Translate business and product priorities into a clear engineering roadmap, delivery plan, and team-level objectives.
- Recruit, onboard, manage, and retain engineers with the skills required to build production-grade AI and agentic systems.
- Establish clear ownership, performance expectations, decision-making responsibilities, and development plans across the team.
- Drive predictable execution through effective planning, dependency management, risk identification, and operational readiness.
- Partner with senior individual contributors to guide architecture and technical direction without becoming a bottleneck for engineering decisions.
- Ensure consistent engineering practices across AI evaluation, observability, model governance, security, reliability, performance, and cost management.
- Collaborate with Product, Architecture, Security, Data, Legal, and product engineering teams to deliver enterprise-ready AI capabilities.
- Balance shared platform investments with customer-facing requirements and immediate product priorities.
- Monitor delivery, quality, platform adoption, incidents, operational performance, ...
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