Director of Research & Development

We are seeking a technically strong, commercially aware Director of R& D to lead our multidisciplinary research and development team across software, hardware, firmware, computer vision, applied AI, prototyping, and testing. Based in India and reporting directly to the CTO, you will turn emerging technologies and complex business problems into validated capabilities for future products and platforms.

You will combine technical judgment with people leadership: shaping the innovation portfolio, challenging assumptions, guiding experiments, and building integrated prototypes and developing the team. You will lead all disciplines within R& D and coordinate contributions from global specialists, working closely with Product, Architecture, Software Engineering, Hardware Engineering, Quality, and Operations. Core mandate: Discover, prove, and de-risk new technology, then enable an agreed transition into product engineering.

The core responsibilities for the job include the following:

Shape the innovation portfolio:

• Translate the CTO's technology direction into a focused R& D roadmap.
• Maintain a common backlog of customer-led opportunities and technology-led ideas, prioritized with the CTO and product leadership.
• Identify new possibilities proactively rather than waiting only for product requirements.
• Define each initiative's hypothesis, intended value, resource ceiling, success measures, review date, and stop criteria; recommend when to continue, redirect, partner, or stop.

Lead the entire multidisciplinary R& D team:

• Build, mentor, and manage engineers, researchers, technical leads, and test specialists across software, hardware, firmware, and computer vision.
• Establish clear ownership, development plans, and performance expectations.
• Create integrated project teams rather than disconnected discipline silos, and resolve cross-team dependencies.
• Work effectively with global colleagues while developing strong technical leadership and execution capability in India.

Provide hands-on technical and systems leadership:

• Lead architecture discussions, design reviews, experiments, and difficult root-cause investigations.
• Challenge assumptions across sensing, electronics, firmware, algorithms, applications, and system behavior.
• Guide trade-offs involving accuracy, latency, compute, power, cost, reliability, and integration.
• Stay close enough to the engineering evidence to distinguish a credible result from a promising demonstration, while empowering specialists to own detailed implementation.

Move concepts into validated prototypes and controlled pilots:

• Own progression from feasibility to integrated prototypes and approved trials.
• Agree on acceptance criteria and the receiving engineering owner early.
• Deliver reproducible builds, source code, firmware, relevant hardware designs and bills of materials, model and dataset records, test evidence, and documented limitations.
• Support productization through an accepted handover to the responsible Engineering and HWE teams; do not treat a demonstration as a production release.

Make testing and research evidence central:

• Embed testing from the first experiment, with repeatable benchmarks, instrumentation, and traceable results.
• Develop simulation, automated testing, and hardware-in-the-loop capability.
• Validate whole-system performance under realistic operating conditions, including lighting changes, occlusion, chip configurations, device variation, and failure scenarios.
• Address security, privacy, reliability, manufacturability, serviceability, and certification considerations early, in partnership with the relevant specialists.

Scout emerging technology and protect intellectual property:

• Evaluate relevant advances in RFID, sensing, embedded computing, computer vision, AI, communications, and human-machine interaction.
• Build purposeful relationships with universities, technology partners, suppliers, and research organizations.
• Assess build-versus-buy-versus-partner options against measurable value, feasibility, and lifecycle cost.
• Capture inventions and technical knowledge, supporting patent evaluation, confidentiality, and third-party IP review with the appropriate experts.

Run an accountable, visible R& D operation:

• Manage people, laboratories, equipment, vendors, and project budgets within CTO-approved plans.
• Publish clear progress, experimental evidence, risks, capacity constraints, and decisions required.
• Use approved AI-assisted engineering and automation tools where they improve measurable outcomes.
• Collaborate with the separate AI Engineering function without duplicating its mandate, and coordinate productization capacity with Engineering rather than creating unplanned delivery or support commitments.

Requirements:

• Leadership experience. Typically 15+ years in engineering, applied R& D, or technology development, including 5+ years leading multidisciplinary teams, technical leaders, or complex product-development programs.
• Integrated product development. A demonstrated record of taking new technologies from concept through experimentation, prototypes, and validation into products used in real operating environments. Experience must span software and physical-device or embedded-system development, not solely application delivery.
• Technical depth and breadth. Deep expertise in at least one relevant discipline, with credible working knowledge across software, electronics, firmware, computer vision, and system validation. Able to challenge specialist decisions and understand interfaces without being the principal expert in every field.
• Research and engineering judgement. Strong capability in experimental design, quantitative evaluation, systems thinking, technical risk assessment, and root-cause analysis. Comfortable with incomplete requirements and willing to change direction when evidence contradicts an assumption.
• Practical development fluency. Experience working with software and embedded development environments, source control, automated testing, and technical documentation. Familiarity with relevant technologies such as C/C++, Python or Java, embedded Linux or real-time systems, and vision or machine-learning tooling; mastery of every listed technology is not required.
• People and stakeholder leadership. Proven hiring, coaching, performance management, and cross-functional leadership skills. Able to communicate technical trade-offs clearly to executives, product, customers, and partners and collaborate effectively across geographies and time zones.
• Education. Bachelor's or master's degree in computer science, electronics, electrical engineering, computer engineering, robotics, or a related field. A PhD in a relevant discipline is preferred but not mandatory; practical innovation and product-development outcomes are essential.
• Experience that would be particularly valuable: RFID or RF systems; sensor fusion; edge AI; computer vision in uncontrolled environments; industrial automation; robotics; connected devices; automotive electronics; medical devices; or other high-reliability products.
• Exposure to regulated gaming, manufacturing partners, prototype-to-production transfer, invention disclosures, or university collaboration would be an advantage. Prior casino-industry experience is useful, but not essential.

Skills

AI, R&D, RFID, computer vision, development, electronics, embedded, firmware, hardware, machine learning, research