Engineering Manager, AI

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Skills you'll use

What you'll do

• Engineering Leadership
• Build, mentor, and manage a team of 15–30 software engineers, architects, and technical leads.
• Advance engineering excellence through strong software development practices, architecture reviews, code quality, and operational rigor.
• Foster a culture of innovation, ownership, accountability, continuous learning, and customer focus.
• Establish career development plans, coaching frameworks, and performance processes for engineers.
• AI Platform, Architecture, Governance and Security
• Lead the design, development, and delivery of enterprise-grade AI-native SaaS platforms focused on AI governance, compliance, policy enforcement, MCP security, AI risk management, and security analytics.
• Define and execute the technical roadmap for scalable, resilient, multi-tenant cloud-native systems aligned with business priorities and customer needs.
• Shape architectural direction across AI and platform services, including LLM integrations, AI gateways and proxies, security enforcement frameworks, event-driven architectures, and workflow orchestration systems.
• Establish and promote secure AI development practices, including controls for policy enforcement, prompt security, agent and MCP governance, audit logging, observability, and operational resilience.

Who can apply

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.
• 12+ years of software engineering experience, including 4+ years leading engineering teams in a product development environment.
• Proven experience building and delivering enterprise-scale SaaS platforms using cloud-native architectures and distributed systems.
• Strong technical expertise in Generative AI, Large Language Models (LLMs), AI agents, and AI application architectures.
• Hands-on experience designing and integrating AI platforms, model services, APIs, and enterprise AI workflows.
• Deep understanding of software architecture, microservices, Kubernetes, containers, event-driven systems, and high-availability design principles.
• Experience implementing security, governance, compliance, and risk management controls within enterprise software products.
• Strong knowledge of public cloud platforms such as AWS, Azure, or GCP, including DevOps and observability practices.
• Demonstrated ability to guide engineering execution, mentor technical leaders, and establish strong engineering practices across teams.
• Excellent communication, judgment, stakeholder management, and problem-solving skills, with the ability to influence technical and business outcomes.

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