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Engineering Manager, AI Experience: 12+ years Location: Bangalore / Coimbatore (Hybrid) About AppViewX AppViewX is trusted by leading organizations around the world to reduce risk, ensure compliance, and increase visibility through machine identity management, AI security governance, and application infrastructure security. We are building next-generation platforms that help enterprises discover, govern, secure, and manage AI agents, MCP servers, models, identities, and workflows across coding and non-coding environments. As enterprises accelerate adoption of Agentic AI, LLMs, autonomous agents, and AI-powered workflows, AppViewX is enabling organizations to embrace AI innovation securely while maintaining governance, compliance, and operational resilience. At AppViewX, you will work on the AVX ONE platform, which delivers certificate lifecycle management and PKI-as-a-Service through streamlined automation workflows designed to prevent outages, reduce security incidents, and support crypto-agility. Role Overview We are looking for an experienced Engineering Manager, AI to guide a high-impact team building enterprise-grade AI security, governance, and agent management platforms. This role combines engineering leadership with strong technical depth in AI/ML systems, LLMs, distributed systems, cloud-native architectures, and security. You will help shape architecture, delivery, reliability, scalability, and security for AI-native products while mentoring high-performing engineering teams. The ideal candidate is comfortable working across agent frameworks, distributed systems design, scalability, security controls, compliance requirements, and engineering execution. Key Responsibilities 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. Ensure platform reliability, performance, scalability, and security using distributed systems principles, cloud-native technologies, and engineering best practices. Partner closely with Product Management, Security Research, Customer Success, and GRC teams to deliver solutions aligned with frameworks such as SOC 2, ISO 27001, NIST AI RMF, and OWASP LLM Top 10. Reliability and Operations Promote operational excellence through observability, monitoring, incident management, and SRE best practices. Define SLAs, SLOs, and reliability goals for AI and platform services. Lead production readiness reviews and post-incident improvement efforts. Drive cloud cost optimization and platform efficiency initiatives. Stakeholder Management Communicate technical vision, risks, trade-offs, and progress to executive stakeholders. Partner with customers and field teams to understand enterprise AI adoption challenges. Translate custome