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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Gateway Engineer - **Company:** Dexian DISYS - **Location:** Jackson, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Cyber Security, Information Leak Prevention, Identity and Access Management, PCI Data Security Standards, Zero Trust Network Access, Azure Machine Learning, Systems Integration, Data Logging, Load Balancing, Snowflake, Grafana, Multi-Cloud, Caching, Rate Limiting, AI Platforms, Information Technology, Deployment Automation, Data Management - **Published:** August 27, 2026 - **Apply:** https://www.dice.com/job-detail/f4b983f2-4730-48ef-ad53-56fb3d4f74b7 ## About the Role * Bachelor's degree in Computer Science, Cyber Security, Information Technology, Engineering, or related field; master's degree preferred. * Over 8 years of experience designing and operating enterprise cloud, API, or application platforms. * At least 5 years of experience in cloud architecture and security. * Minimum of 3 years working with AI/ML platform technologies or enterprise AI deployments. * Proven experience with implementing and managing enterprise gateway solutions. * Experience working within regulated industries such as financial services or capital markets. Preferred Qualifications * Certification as a Kong Certified Professional. * Certification as an AWS Solutions Architect. * Certification as a Microsoft Azure Solutions Architect. * Security certifications such as CISSP or CCSP. * Experience implementing AI security controls and governance frameworks. * Familiarity with industry standards and regulations such as NIST AI RMF, NIST 800-53, NYDFS 500, PCI DSS, or SOC 2. * Experience with enterprise data protection controls like DSPM and DLP. ## Description We are seeking a highly skilled Senior AI Gateway Engineer to lead the design, development, security, and operational management of our enterprise AI Gateway platform. This role focuses on utilizing leading gateway technologies to enable secure, resilient, and compliant access to large-scale AI models, AI agents, and related services across the organization. The ideal candidate will leverage expertise in cloud architecture, security, identity management, and enterprise governance to create a highly available AI platform capable of supporting regulated environments., * Design, implement, and enhance enterprise AI Gateway solutions using leading gateway technologies. * Develop standardized onboarding processes for applications, AI agents, and business services utilizing AI. * Engineer reusable integration patterns for various AI providers and internal/external AI services. * Implement intelligent routing, failover mechanisms, traffic shaping, and provider abstraction. * Create custom plugins and integrations that support AI governance and security requirements. * Define scalable architectures for control and data planes across hybrid and multi-cloud environments. * Architect and implement enterprise-grade identity controls, integrating with enterprise identity providers. * Establish fine-grained authorization at multiple levels, including models, agents, and data sources. * Partner with security teams to implement AI governance frameworks, including Zero Trust principles. * Deploy AI security guardrails, including prompt injection prevention, data loss prevention, PII redaction, and content safety. * Establish policy-as-code practices for managing AI controls at scale. * Define logging, monitoring, and audit procedures supporting compliance. * Design highly available, resilient AI platform architectures incorporating multi-region deployment, failover, and cross-cloud recovery. * Implement traffic management features such as rate limiting, circuit breakers, load balancing, and caching. * Define and manage operational metrics, error budgets, and recovery objectives. * Conduct resilience testing, architecture reviews, and failure scenario exercises. * Design AI access patterns across multi-cloud platforms such as Azure, AWS, and Snowflake. * Integrate AI Gateway services with various data platforms and observability tools. * Build monitoring dashboards and support incident response and troubleshooting activities. ## Related Videos - [HTTP headers that make your website go faster](https://www.wearedevelopers.com/videos/1676-http-headers-that-make-your-website-go-faster) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Building Sovereign AI: Lessons from Deploying Secure RAG Systems using Confidential Computing](https://www.wearedevelopers.com/videos/100108-building-sovereign-ai-lessons-from-deploying-secure-rag-systems-using-confidential-computing) - [Event based cache invalidation in GraphQL](https://www.wearedevelopers.com/videos/433-event-based-cache-invalidation-in-graphql) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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