Operations Technology Solutions Architect - Specialist Master

About This Role

Lead and mentor multidisciplinary engineering teams to design, architect, and implement comprehensive hybrid edge AI solutions for clients' Operations Technology (OT) automation and intelligence needs, leveraging cutting-edge engineering capabilities to drive innovation and transformation.

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 environment
• Bring together varied technologies including AI, GenAI, Agentic solutions, Edge-cloud infrastructure, IIoT sensor & devices data, sensor fusion and varied systems integrations to design and implement specific solutions
• Manage full operations lifecycle for hybrid edge AI solutions engagements for clients including managing work breakdown for the team, project planning, day-to-day engineering delivery, integration of parts and delivery of complete solutions
• Ensure that OT solutions design comply with industry best-practices for solution design and with relevant industry standards and regulations, such as NERC CIP, ISA/IEC 62443
• Provide technical leadership, mentorship to your team towards technology choices, troubleshooting, engineering best practices, technology implementation guidance and day-to-day execution support
• Identify opportunities for expanding AI-driven automation and intelligence within client operations
• Oversee edge and AI infrastructure operations, including monitoring, reliability engineering, and AI-driven operations enablement

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
• Hands-on experience with OT data enablement, analytics implementation, AIML solution development
• In-depth understanding of cluster build/containers, manage 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
• Legally authorized to work in the United States without the need for employer sponsorship

Qualifications

• A 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 etc.
• 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 both technical and non-technical stakeholders

Skills

* Required skills