Operations Technology Solutions Architect - Specialist Master

About This Role

Lead and mentor a multidisciplinary engineering team to develop and architect comprehensive hybrid edge AI solutions for clients, focusing on integrating with existing operations technology and IT infrastructure. Your work will significantly impact client success by reimagining critical operations and processes.

Responsibilities

• Lead, mentor, and manage a multidisciplinary team of engineers specializing in AI, machine learning, edge computing, and distributed systems
• Develop and architect comprehensive hybrid edge AI solutions that integrate seamlessly with existing OT/IT infrastructure and cloud environments
• Integrate varied technologies including AI, GenAI, Agentic solutions, Edge-cloud infrastructure, IIoT sensor & devices data, sensor fusion, and systems integrations to design and implement client solutions
• Manage the full operations lifecycle for hybrid edge AI solution engagements, including project planning, engineering delivery, and solution integration
• Ensure OT solutions design complies with industry best practices and relevant standards and regulations (e.g., NERC CIP, ISA/IEC 62443)
• Provide technical leadership and mentorship to the team on technology choices, troubleshooting, engineering best practices, and implementation guidance
• Ensure solutions are scalable, secure, reliable, and optimized for Operations Technology (OT)
• Oversee edge and AI infrastructure operations, including monitoring, reliability engineering, and AI-driven operations enablement
• Identify opportunities for expanding AI-driven automation and intelligence within client operations

Requirements

• 8+ years of managing multi-disciplinary teams of engineers delivering end-to-end solutions
• 3+ years' experience of edge computing architectures, distributed systems, and real-time data processing
• 2+ years with OT protocols (e.g., OPC-UA, Modbus, MQTT) and integration with industrial control systems
• 3+ years of AI/ML algorithm framework (e.g. Pytorch, TensorFlow) and their application in edge environment
• 3+ years' experience with architecture, design expertise for AI solutions for cross-industry OT applications
• Strong knowledge and implementation experience with cloud provider edge stacks (AWS, GCP, Azure) and hybrid-edge infrastructure providers (Dell, HPE, Qualcomm and NVIDIA)
• Proven track record of delivering AI/ML solutions in edge computing, IoT, or distributed infrastructure environments, preferably within Operations Technology (OT) domains
• Hands-on experience with OT data enablement, analytics implementation, AIML solution development
• In-depth understanding of cluster build/containers, managing edge services (pub/sub, object/block storage), and server/container networking
• Extensive hands-on experience in deploying, configuring, and activating edge infrastructure to meet specific application requirements
• Ability to travel up to 50% on average
• Legally authorized to work in the United States without employer sponsorship

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, or a related field, or equivalent experience
• 8+ years of managing multi-disciplinary teams of engineers delivering end-to-end solutions, 3+ years' experience of edge computing architectures, distributed systems, and real-time data processing, 2+ years with OT protocols and integration with industrial control systems, 3+ years of AI/ML algorithm framework and their application in edge environment, 3+ years' experience with architecture, design expertise for AI solutions for cross-industry OT applications

Nice to Have

• Experience in edge and AI infrastructure operations, including monitoring, site reliability engineering
• OT relevant certs: TOGAF/ICS/CSSA
• Proficiency in securing OT environments against cyber threats, ensuring compliance with standards like NIST and IEC 62443
• Experience in evaluating, selecting, and managing vendors to ensure high-quality service delivery
• Proficiency in network design and management, including understanding of protocols and communication standards used in OT environments
• Understanding of cybersecurity best practices and compliance requirements in OT and edge computing contexts
• Ability to manage complex projects, coordinate cross-functional teams, and communicate effectively with stakeholders

Skills

* Required skills