Summary: Seeking an AI Engineering Manager to lead the design and delivery of secure, cloud-native GenAI capabilities, including full-stack applications, AI agents, and platform components, while mentoring engineers and driving project outcomes. Highlights: 1. Shape architecture and delivery of secure, cloud-native GenAI capabilities 2. Lead design and implementation of full-stack applications and AI agents 3. Mentor engineers and drive larger project outcomes with a leadership mindset We are building secure, cloud\-native GenAI capabilities and need an **AI Engineering Manager** to shape architecture and delivery. You will design and implement full\-stack applications, AI agents, and platform components that accelerate GenAI agent development, validation, and deployment. Bring your leadership mindset and apply today **Responsibilities** * Design and deliver full\-stack applications, AI agents, and platform components * Create developer tooling, CI/CD pipelines, and observability to enable safe, rapid iteration * Implement secure SDLC practices and privacy\-by\-design controls * Partner with product, UX, and domain experts to ship client\-focused solutions * Apply modern LLM patterns to produce measurable client value * Lead by example, steer architecture, mentor engineers, and own larger project outcomes **Requirements** * 8\+ years of professional software engineering experience * Strong full\-stack development skills and cloud experience (AWS/Azure/GCP) * Expertise in at least one area, with solid capability across the others: AI Agent development and evaluation, Backend development, Frontend development * Hands\-on experience with cloud services (AWS/Azure/GCP), CI/CD and Infrastructure as Code, Site Reliability Engineering (SRE) * Strong knowledge of quality engineering/testing strategy, Secure SDLC and privacy by design * Proven track record delivering secure, reliable, cloud\-native systems to production * Upper\-Intermediate English language proficiency (B2\) **Nice to have** * Ability to ship software products independently or within a small, fast\-paced team * Experience taking AI agents from concept to production, including safety evaluations and iterative testing * Exposure to LangChain/LangGraph and MCP; vector/RAG systems; OpenSearch * Background in traditional ML tasks such as training, deployment, and monitoring * Understanding of how LLMs work, common failure modes, and approaches like fine\-tuning and model adaptation * Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.