• Design and implement scalable AI service architectures in cloud environments (Azure preferred; AWS or GCP acceptable) • Build event-driven systems using queues and messaging platforms (e.g., Azure Service Bus, RabbitMQ, SQS) to support asynchronous AI workloads. • Implement event streaming and real-time processing pipelines (e.g., Kafka, Azure Event Hubs, Pub/Sub, Kinesis). • Architect, maintain, and scale containerized AI services deployed to Kubernetes, with emphasis on Azure Kubernetes Service (AKS). • Design orchestration layers that manage model calls, downstream services, retries, rate limits, and failure handling. • Optimize system performance under load, including horizontal scaling, autoscaling policies, resource management, and cost control. • Implement WebSocket or real-time client communication patterns for interactive AI applications. • Contribute to infrastructure-as-code and CI/CD practices for AI service deployment, collaborating with CloudOps, DevOps, and application engineering teams to ensure reliability, availability, and operational standards are met. • Partner with Product and business stakeholders to translate projected traffic, adoption, and growth targets into scalable technical architectures and capacity plans and debug production level issues as needed.

­Led by an experienced management team and supported by a strong investor group, including large and experienced institutions and strategic partners, EdgeConneX offers a dynamic, fast-paced work environment where we are bringing flexibility, proximity, power, and connectivity to some of the world’s key businesses. With major offices in Herndon, Denver, and Amsterdam, we have a global footprint and a unified team of employees committed to providing a premier customer experience and delivering the full spectrum of data center solutions, from core to edge, like no other data center provider can do. Focused on driving innovation and helping our customers define and deliver their own unique vision for the Edge, at any scale, in any market worldwide, for any requirement, we are building tomorrow’s data center infrastructure, today for some of the world’s most demanding Network, Content, and Cloud customers. EdgeConneX is seeking a Senior Director of Cloud Services & Hybrid Infrastructure to lead the transformation of our IT/OT landscape from an Azure-centric model into a resilient, hybrid multi-cloud enterprise. This is a hands-on "Builder-Leader" role — you will be responsible for ensuring our cloud-based products and enterprise systems remain secure and best-in-class while integrating seamlessly with our on-premise industrial assets. Beyond cloud modernization, this role will build the infrastructure foundation required to enable AI across EdgeConneX's product lines and operations. The ideal candidate combines deep technical expertise in cloud platforms, automation, and cost optimization with the leadership skills to upskill teams and drive a platform engineering mindset. While a senior leadership position, this position will not initially oversee an internal engineering team. This position can be based remotely on the East Coast of the U.S., the ideal candidate would be based in our Herndon, VA headquarters with the majority of the team. There will be limited travel (10-20%) associated with this role. Responsibilities Hybrid Strategy & OT Convergence - Architect the connectivity and data flows between OT environments and cloud-based SaaS products. - Own the stability, security, and performance of hybrid connectivity (ExpressRoute, Site-to-Site VPNs, SD-WAN) across IT and OT boundaries. Multi-Cloud Expansion & Optimization - Lead the evolution from a primarily Azure environment into a strategic multi-cloud footprint (AWS, GCP) to leverage specialized services and reduce vendor lock-in. - Drive cloud management and optimization initiatives — establish resource right-sizing, reserved instance strategies, and workload placement policies. - Implement automated governance and FinOps practices to ensure 100% transparency in hybrid spend, including advanced automation for resource provisioning and cost-tagging. Virtualization to Container Modernization - Define and execute the roadmap for migrating legacy virtualized workloads to containerized, cloud-native architectures. - Establish Kubernetes-based platforms for running production workloads as appropriate, shifting the organization toward modern orchestration patterns. Automation & Platform Engineering - Drive an "automation-first" culture using Infrastructure as Code (Bicep, Terraform) to replace manual processes with self-healing, self-service infrastructure. - Oversee the design, architecture, and management of DevOps CI/CD pipelines across the application portfolio. - Build secure dev, test, and production environments that accelerate software delivery with a platform-as-product mindset. - Ensure infrastructure fungibility and that DR solutions are robust and resilient. AI Infrastructure Enablement - Build and scale the high-performance computing (HPC) and data environments required to deploy AI technologies across EdgeConneX product lines. - Partner with application and data teams to ensure cloud infrastructure is ready to support AI/ML workloads, including training, fine-tuning, and inference. - Evaluate and recommend AI/ML infrastructure services across cloud providers to support the company's AI roadmap. Leadership & Governance - Lead, mentor, and grow a team of infrastructure and platform engineers — with a track record of upskilling legacy IT teams into modern DevOps and cloud-native practitioners. - Partner with security teams to implement DevSecOps, ensuring compliance with zero-trust principles and data protection policies. - Work with leadership and PMO to manage workstreams across internal teams and contractors. Required Qualifications - 10+ years in technology, with at least 5+ years focused on cloud infrastructure, platform engineering, and leading teams. - Hands-on experience managing hybrid environments across data centers and public clouds (AWS, Azure, GCP). - Deep expertise in cloud cost management and FinOps tooling and practices. - Strong hands-on experience with Infrastructure as Code (Terraform, Bicep, Ansible) and scripting (Python, PowerShell, Bash). - Demonstrated experience migrating virtualized workloads to container-based architectures (Kubernetes, Docker). - Deep knowledge of hybrid networking: ExpressRoute, Site-to-Site VPNs, SD-WAN for IT/OT security. - Understanding of the cost-benefit analysis of build vs. buy — ability to articulate when to use Azure vs. GCP/AWS for specific IoT telemetry, data analytics, and AI workloads. - Strong experience leading engineering teams and influencing senior leadership. Preferred Qualifications - Experience in data center, critical facilities, or industrial/OT technology environments. - Experience providing infrastructure for AI/ML workloads, including GPU orchestration and HPC environments. - Familiarity with LLMOps, RAG architectures, or MLOps tooling. - Experience with GitOps practices for infrastructure configuration management. - Familiarity with next-generation IaC tools (Crossplane, Pulumi). - Track record of implementing FinOps programs with measurable cost reduction outcomes. - Experience with Agile/DevOps practices at scale. EdgeConneX believes inclusion – of thought, backgrounds and experiences – affects all that we do, from our employees to the solutions we deliver. Our goal is to create an environment where embracing differences helps deepen the lives and work experience of our employees, enhances our innovation and creativity, and enriches our involvement in our communities. EdgeConneX is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or ancestry, physical or mental disability, as well as any other category protected by applicable federal, state, or local laws. EdgeConneX offers a competitive benefits package. For more information on how we process your data, visit our Data Privacy Policy here.

Overview: We are seeking a highly skilled and experienced Genesys Cloud Engineer to play a pivotal role in the design, implementation, and optimization of our new Genesys Cloud Contact Center and Unified Communications (UC) systems. As a key member of our Telcom Services team, you will be responsible for translating business requirements into robust technical solutions, ensuring a seamless migration and integration with existing enterprise systems. This role requires deep technical expertise in Genesys Cloud, strong problem-solving abilities, and excellent collaboration skills to work with various stakeholders across the organization. Location: Remote Preferred Qualifications: - Genesys Cloud Certified Professional or Genesys Cloud Certified Architect certification(s). - Proficiency in scripting languages (e.g., Python, PowerShell) for automation or custom integrations. - Experience with identity management solutions (Azure AD) and SCIM provisioning. - Experience with reporting tools and analytics within Genesys Cloud. - Prior experience migrating from legacy on-premise contact center/UC systems (e.g., Cisco, Avaya, Genesys Engage) to a cloud platform. Job Description Ensures integrity of the network devices, communication systems software, hardware. Identifies, programs and maintains all network and communication applications. Assists and participates in the review and design of new or existing network infrastructure and systems. Develops and conducts in-service training on new applications. Job Responsibility 1.Responsible for engineering and integrity of the networking and communication system’s software, hardware, and configurations. 2.Responsible for identifying, engineering/designing and programming of networking infrastructure and communication applications. 3.Develops knowledge base documents and conducts knowledge transfer among engineering team. 4.Assists in the review and evaluation of project requests and recommends appropriate action. 5.Administers installation and repair services. 6.Responsible for first level problem resolution for all health system locations. 7.Gives guidance and direction to engineering team and outside service technicians. 8.Operates under limited guidance and work assignments involve moderately complex to complex issues where the analysis of situations or data requires in-depth evaluation of variable factors. 9.Performs related duties as required. All responsibilities noted here are considered essential functions of the job under the Americans with Disabilities Act. Duties not mentioned here, but considered related are not essential functions. Job Qualification •Bachelor's Degree required, or equivalent combination of education and related experience •3-5 years of relevant experience, required. *Additional Salary Detail The salary range and/or hourly rate listed is a good faith determination of potential base compensation that may be offered to a successful applicant for this position at the time of this job advertisement and may be modified in the future.When determining a team member's base salary and/or rate, several factors may be considered as applicable (e.g., location, specialty, service line, years of relevant experience, education, credentials, negotiated contracts, budget and internal equity).

• Analyze and research cloud-native tools and frameworks to design innovative Google Cloud Platform (GCP) solutions that meet client requirements. • Support the T-Systems Public Cloud Product Management Team to build and define solutions based on customer and market feedback. • Contribute to the implementation of cloud solutions, automation, and service improvement initiatives using Google Cloud technologies. • Participate in technical workshops and assist in pilot and proof-of-concept projects. • Collaborate with senior architects and engineers to review client workloads, provide technical support, and align solutions with Google Cloud best practices. • Assist in client proposals and presentations throughout the customer engagement lifecycle, from pre-sales to implementation. • Support the review of existing customer environments to identify areas for improvement, including cloud migration planning using Google Cloud services. • Build and customize automated cloud-native solutions, applying Infrastructure-as-Code (IaC) principles with tools such as Terraform or Cloud Deployment Manager. • Contribute to the solution portfolio by creating templates, defining new features, and preparing technical documentation. • Collaborate with DevOps teams and support troubleshooting efforts for cloud-based system environments.