Technology Analysts – Industrial AI & OT for Pharma and Energy

Bring your operational technology experience in energy or pharmaceutical manufacturing to research how AI can create safe, scalable value in industrial operations and supply chains. ARC is expanding its analyst team in Bangalore and is seeking two Technology Analysts with strong industrial and operational technology perspectives. We are particularly interested in candidates who have worked in, advised, researched, or supplied technology to pharmaceutical manufacturing or energy operations and can analyze how artificial intelligence is being adopted, integrated, governed, and scaled in these environments. The research mandate focuses on the intersection of AI and OT: how organizations combine software-based and physical AI with industrial automation, control systems, MES and manufacturing operations management, historians and industrial data, asset performance systems, robotics, autonomous systems, enterprise applications, and workforce expertise. In pharmaceutical manufacturing, this includes regulated production, quality, validation, batch operations, data integrity, and reliable technology deployment. In energy, it includes power generation and utilities, oil and gas, renewables, field and plant operations, asset reliability, process safety, and critical infrastructure. The strongest candidates will bring practical familiarity with OT users, architectures, suppliers, operating constraints, and investment priorities in pharma or energy, along with technology knowledge, rigorous research, and clear business writing. The two positions may have complementary specialties across these sectors, industrial operations, supply chain, enabling technologies, and AI governance. What You Will Cover Enterprise and industrial AI strategies, including the progression from pilots and point solutions to repeatable, governed, enterprise-scale deployment. AI and physical AI applications across production, quality, maintenance, engineering, energy, asset performance, safety, and frontline operations—including robotics, autonomous mobile systems, machine vision, intelligent equipment, and human-machine collaboration. AI applications across demand planning, sourcing, procurement, inventory, logistics, distribution, supplier management, and supply-chain resilience. The OT and software foundations for scaled AI, including distributed and supervisory control systems, PLCs, SCADA, MES and manufacturing operations management, historians, asset performance and maintenance systems, ERP, industrial data platforms, cloud and edge infrastructure, and digital twins—especially in regulated pharmaceutical plants and safety- and reliability-critical energy operations. Industrial AI governance, including data and model governance, cybersecurity, functional and operational safety, human oversight, accountability, transparency, regulatory and policy requirements, vendor risk, intellectual property, responsible AI, and lifecycle monitoring for deployed systems. Workforce implications, operating-model changes, process redesign, and the organizational capabilities needed to convert AI investments into sustainable business outcomes. The competitive landscape, capabilities, partnerships, positioning, and strategies of technology suppliers serving industrial operations and supply chains. Adoption patterns, investment priorities, use cases, barriers, suppliers, and measurable value in pharmaceutical manufacturing and energy, with additional coverage of other process, hybrid, discrete, and infrastructure sectors where relevant. Key Responsibilities Research global technology and market trends through executive and practitioner interviews, secondary research, surveys, data analysis, and ongoing engagement with industrial companies and technology suppliers. Track how organizations select, deploy, integrate, govern, and scale software-based and physical AI across operational and supply-chain environments, including the controls used to manage safety, security, compliance, model performance, human oversight, and accountability. Build relationships with AI providers, industrial software and automation suppliers, cloud and data companies, manufacturers, asset-intensive operators, consultants, and subject-matter experts. Write clear, insightful market research reports, technology evaluations, supplier analyses, case studies, and executive-level commentary. Analyze market opportunities, customer requirements, competitive dynamics, adoption barriers, value drivers, and emerging business models. Present findings in client briefings, webinars, conferences, ARC forums, and internal discussions. Support ARC advisory and consulting engagements by translating complex AI and industrial technology developments into practical business implications. Collaborate with ARC analysts in India and other regions to create consistent global research and connect AI developments across technology domains and industries. Contribute ideas for new research, data products, client services, and AI-enabled analyst workflows. What We Are Looking For OT sector experience is a priority: professional experience in pharmaceutical manufacturing or energy—including power and utilities, oil and gas, renewables, or other asset-intensive energy operations—or with a technology supplier, engineering firm, research organization, or consultancy serving these sectors. Working knowledge of operational technology environments such as industrial automation and control systems, MES or manufacturing operations management, SCADA, historians and industrial data platforms, asset performance and maintenance systems, machine and equipment connectivity, or plant and field operations. Knowledge of artificial intelligence and the ability to assess how AI integrates with OT, enterprise applications, engineering and operational workflows, data foundations, safety requirements, and human decision-making. Ability to understand complex technologies and explain how they create business value, change workflows, affect operating models, and address the reliability, quality, safety, cybersecurity, and compliance requirements of industrial environments. Strong analytical thinking, curiosity, interviewing skills, attention to detail, and the ability to distinguish market momentum from deployable, scalable value. Excellent written and spoken English, including the ability to produce professional research and deliver confident presentations. Ability to work independently, manage multiple research priorities, collaborate across time zones, and apply a relevant degree in engineering, automation, computer science, information technology, operations, business, science, or a related discipline. Preferred Experience Direct experience in a pharmaceutical manufacturing or energy organization, or in an automation, industrial software, engineering, consulting, research, or technology supplier role serving those industries. For pharma: familiarity with regulated manufacturing, batch processes, quality operations, validation, data integrity, process automation, MES, laboratory or production systems, and GxP operating requirements. For energy: familiarity with power generation and utilities, oil and gas, renewables, transmission and distribution, field and plant operations, process control, asset reliability, process safety, or critical infrastructure. Understanding of industrial software and OT architectures, including how control systems, MES, SCADA, historians, asset performance systems, ERP, data platforms, cybersecurity, cloud, and edge environments interact. Familiarity with generative AI, machine learning, industrial AI, agentic systems, computer vision, robotics, autonomous systems, intelligent equipment, optimization, or AI-enabled decision support, together with responsible AI and governance considerations. Experience conducting market sizing, forecasting, competitive analysis, supplier evaluations, use-case research, or technology-adoption studies, and existing relationships in pharma, energy, or industrial technology communities. Experience using AI tools to improve research, analysis, knowledge management, or content development. Why Join ARC Help define ARC’s research agenda around one of the most important themes in industrial technology: scaling AI across industrial operations and supply chains. Build a visible analyst profile at the intersection of AI, industrial systems, operating transformation, and business value. Work on global research while contributing to the continued growth of ARC’s Bangalore team. Engage directly with senior technology leaders, suppliers, and industrial companies around the world. Join a collaborative organization focused on the technologies transforming industry, energy, and infrastructure.