1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead architecture and delivery of secure, scalable IT/OT, Industrial AI, plant connectivity, and Smart Manufacturing solutions.
- Define architectures connecting OT assets, PLCs, DCS, SCADA, historians, MES/MOM, edge systems, enterprise applications, and cloud platforms.
- Design industrial data pipelines and integrations for production, quality, maintenance, energy, event, and time-series data.
- Lead Industrial AI and Edge AI use cases including predictive maintenance, anomaly detection, computer vision, process optimization, and energy management.
- Establish standards for asset hierarchies, Unified Namespace, semantic models, contextualization, metadata, and data quality.
- Design OT cybersecurity, network segmentation, identity, encryption, remote access, redundancy, and disaster recovery architectures.
- Lead site assessments, feasibility studies, PoCs, workshops, design reviews, vendor evaluations, demonstrations, RFP/RFI responses, and proposals.
- Govern architecture, integration, testing, DevSecOps/MLOps, documentation, risks, dependencies, quality, and multi-site delivery.
- Provide technical leadership to IT/OT, automation, data, AI, cloud, networking, and cybersecurity teams while coordinating clients, vendors, and delivery partners.
- Develop reusable frameworks, accelerators, reference architectures, and deployment patterns with measurable operational outcomes.
Requirements
- At least 7.5 years of professional experience is required, with 8+ years stated as the expected overall experience in industrial IT/OT, manufacturing connectivity, automation, industrial data, edge computing, cybersecurity, and Industrial AI.
- Bachelor's or master's degree in Electrical Engineering, Electronics and Communication, Instrumentation, Automation, Control Systems, Computer Science, Information Technology, Mechatronics, or a related discipline, with 15 years of full-time education.
- Strong hands-on expertise in industrial IT/OT architecture, factory connectivity, manufacturing integration, edge computing, industrial data engineering, and Industrial AI.
- Deep knowledge of PLCs, DCS, SCADA, HMI, historians, industrial gateways, machine controllers, sensors, drives, robots, and vision systems.
- Advanced knowledge of OPC UA, MQTT, Sparkplug B, Modbus TCP, EtherNet/IP, PROFINET, REST, AMQP, Kafka, and industrial connectivity patterns.
- Experience with high-availability industrial networks, edge architectures, firewalls, switches, routing, VLANs, redundancy, time synchronization, and secure remote access.
- Knowledge of IEC 62443, the NIST Cybersecurity Framework, zero-trust principles, asset inventory, identity and access management, certificate management, patching, and vulnerability management.
- Experience with industrial and cloud ecosystems from Siemens, Rockwell Automation, Schneider Electric, Honeywell, ABB, PTC, Microsoft, AWS, NVIDIA, or equivalent providers.
- Experience with edge and IoT platforms, containerized workloads, Kubernetes, Docker, APIs, message brokers, streaming platforms, and hybrid-cloud architectures.
- Experience integrating OT data with MES/MOM, ERP, PLM, WMS, QMS, EAM/APM, historians, data lakes, lakehouses, Digital Twin, and analytics platforms.
- Experience designing Industrial AI/ML solutions covering data preparation, feature engineering, training, deployment, inference, monitoring, retraining, and responsible AI controls.
- Preferred experience with Python, SQL, REST APIs, scripting, data engineering, analytics, and integration automation.
- Understanding of AI/ML, deep learning, anomaly detection, predictive models, optimization, computer vision, GenAI, and retrieval-oriented industrial knowledge solutions.
- Strong solution architecture, system design, troubleshooting, technical decision-making, client communication, executive stakeholder management, and technical documentation skills.
- Proven experience leading global and distributed multidisciplinary teams and coordinating OEMs, automation vendors, network providers, cloud providers, and delivery partners.
- Preferred certifications include IEC 62443, ISA-95, cloud architecture, networking, cybersecurity, industrial automation, data engineering, AI/ML, Kubernetes, PMP/PMI, or relevant vendor certifications.
Benefits
- The role is based in Bengaluru, India.
- International travel and travel to client manufacturing sites are required based on project needs.
Tech Stack
Categories
Solutions Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.