Custom Software Engineering Lead

Job description

Project Role : Custom Software Engineering Lead Project Role Description : Own the technical direction and architecture of custom software solutions, leading teams through design and delivery. Set development standards and ensure code quality, scalability, and performance aligned to business objectives. Must have skills : Internet of Things (IoT) Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: We are looking for an IT/OT – Industrial AI – Connectivity Lead with 8+ years of experience and strong expertise in IT/OT convergence, industrial connectivity, data platforms, edge computing, automation, cybersecurity, and AI-enabled operations. The candidate will lead solution architecture, technical delivery, and client engagement for Smart Manufacturing, Connected Factory, Industrial AI, and Digital Twin programs across Automotive, Aerospace, CPG, Life Sciences, Resources, and Manufacturing. Strong experience is required in secure industrial connectivity, protocols, data contextualization, streaming, edge/cloud integration, architecture governance, global team leadership, PoCs, RFP/RFI responses, technical workshops, and business development. Roles and Responsibilities: Lead architecture and delivery of secure, scalable IT/OT, Industrial AI, plant connectivity, and Smart Manufacturing solutions. Define reference architectures connecting OT assets, PLCs, DCS, SCADA, historians, MES/MOM, edge, enterprise, and cloud platforms. Assess brownfield/greenfield environments and define current, target, transition, and deployment architectures. Translate manufacturing needs into connectivity, data, contextualization, integration, analytics, and AI solutions. Design industrial data pipelines for real-time and historical production, quality, maintenance, energy, event, and time-series data. Lead Industrial AI and Edge AI use cases including predictive maintenance, anomaly detection, quality/process optimization, computer vision, and energy management. Architect industrial connectivity using OPC UA, MQTT, Sparkplug B, Modbus TCP, EtherNet/IP, PROFINET, REST APIs, and vendor interfaces. Integrate OT with MES/MOM, ERP, PLM, WMS, QMS, EAM/APM, IoT, data platforms, Digital Twin, and analytics. Establish standards for asset hierarchy, Unified Namespace, semantic models, contextualization, metadata, and data quality. Implement OT cybersecurity and resilient architectures covering segmentation, zones/conduits, identity, encryption, remote access, redundancy, and disaster recovery. Lead site assessments, PoCs, feasibility studies, workshops, design reviews, vendor evaluations, and demonstrations. Govern architecture, integration, testing, DevSecOps/MLOps, documentation, risks, dependencies, quality, and multi-site delivery. Provide technical leadership across IT/OT, automation, data, AI, cloud, and cybersecurity teams, including client engagements, RFP/RFI, proposals, estimation, and partner coordination. Develop reusable frameworks, accelerators, reference architectures, and deployment patterns that deliver measurable improvements in downtime, quality, throughput, cost, energy efficiency, and scalability. Professional and Technical Skills: Strong hands-on expertise in industrial IT/OT architecture, factory connectivity, manufacturing integration, edge computing, industrial data engineering, and Industrial AI is mandatory. Deep knowledge of OT systems including PLC, 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/vendor connectivity patterns. Strong understanding of Purdue/ISA-95 architecture, industrial network segmentation, DMZ patterns, zones and conduits, and enterprise-to-plant integration. Experience designing high-availability industrial networks and edge architectures with firewalls, switches, routing, VLANs, redundancy, time synchronization, and secure remote access. Strong understanding of IEC 62443, NIST Cybersecurity Framework, zero-trust principles, asset inventory, identity and access management, certificate management, patching, and vulnerability management. Experience with industrial connectivity and data platforms from Siemens, Rockwell Automation, Schneider Electric, Honeywell, ABB, PTC, Microsoft, AWS, NVIDIA, or equivalent ecosystems. Experience with edge and IoT platforms, containerized workloads, Kubernetes, Docker, APIs, message brokers, streaming platforms, and hybrid-cloud architectures. Strong experience integrating OT data with MES/MOM, ERP, PLM, WMS, QMS, EAM/APM, historians, data lakes, lakehouses, Digital Twin, and analytics platforms. Strong knowledge of industrial data modelling, asset hierarchies, Unified Namespace concepts, semantic models, contextualization, time-series data, event processing, and data governance. Experience designing Industrial AI/ML solutions covering data preparation, feature engineering, training, deployment, inference, monitoring, retraining, and responsible AI controls. Experience with Python, SQL, REST APIs, scripting, data engineering, analytics, and integration automation is preferred. Understanding of AI/ML, deep learning, anomaly detection, predictive models, optimization, computer vision, GenAI, and retrieval-oriented industrial knowledge solutions. Strong understanding of Digital Twin, Industry 4.0, smart manufacturing, connected operations, virtual commissioning, and closed-loop optimization concepts. Experience with observability and operations covering device health, connectivity status, data quality, pipeline monitoring, model performance, logging, alerting, and support processes. Knowledge of manufacturing operations, production systems, maintenance, quality, material flow, utilities, energy management, and industrial engineering. Strong solution architecture, system design, analytical, troubleshooting, problem-solving, and technical decision-making skills. Strong understanding of SDLC, Agile, DevSecOps, DataOps, MLOps, project delivery, technical governance, quality management, and change control. Excellent client-facing communication, executive stakeholder management, workshop facilitation, presentation, and technical documentation skills. Proven experience leading global and distributed teams and coordinating industrial OEMs, automation vendors, network providers, cloud providers, and delivery partners. Strong experience in solution design, PoCs, feasibility studies, technical assessments, site surveys, RFP/RFI responses, effort estimation, and proposal development. Strong understanding of Automotive, Aerospace, CPG, Life Sciences, Resources, Utilities, or General Manufacturing domains. Ability to convert architecture and Industrial AI insights into actionable recommendations, scalable rollout patterns, and quantified business outcomes. Additional Information: Experience: 8+ years of overall experience with significant expertise in industrial IT/OT, manufacturing connectivity, automation, industrial data, edge computing, cybersecurity, and Industrial AI. Location: Bengaluru, India. Travel: Willingness to travel internationally and to client manufacturing sites based on project requirements. Team Leadership: Proven experience leading technical and multidisciplinary teams across OT, IT, data, AI, cloud, networking, and cybersecurity. Education: Bachelor s or Master s degree in Electrical Engineering, Electronics and Communication, Instrumentation, Automation, Contr