Latest Jobs at NTT Ltd.

Your day at NTT DATA

• We are seeking an Intermediate Full Stack Software Engineer to join our IoT Dev team. As an Intermediate Full Stack Software Engineer, you will play a key role in the development and maintenance of our IoT applications and services.

We are looking for individuals with expertise in the following areas.

• C#: Strong background with proven proficiency in C#.
• JavaScript/TypeScript: Solid understanding of JavaScript and TypeScript; experience with Nuxt/Vue is preferred.
• Cloud Platforms: Proficiency in Azure or AWS, with practical experience in deploying and managing applications in cloud environments.
• Kubernetes & DevOps: Hands-on experience with container orchestration (Kubernetes) and DevOps practices, including CI/CD pipelines, automation, and monitoring.
• Software Development Life Cycle (SDLC): Fully engaged and experienced across the software development life cycle.
• Communication Protocols: Practical knowledge of MQTT and other communication protocols.
• Exposure to graph databases: Experience with databases and different types of data storage. Familiarity with graph databases is beneficial for this role (or exposure to Digital Twins \technology).
• IoT and Data: An interest and understanding in Industry 4.0 technologies, IoT (Internet of Things) and Data/AI is highly beneficial.

Nice-to-Have Skills:

• Python: While not required, having experience with Python is a plus.

Responsibilities:

• Collaborate with the development team and clients to gather and analyze requirements and translate them into technical specifications.
• Support multiple on-going projects in challenging environments.
• Participate in the design and architecture of IoT applications and services, focusing on both backend and frontend components.
• Design, develop, and maintain high-quality, reliable, and scalable code following best practices and coding standards.
• Implement and enhance front-end interfaces using relevant frameworks.
• Build and maintain RESTful APIs for seamless integration.
• Conduct unit testing, integration testing, and automated testing to ensure code quality and reliability.
• Optimize application performance, scalability, and security.
• Troubleshoot and debug application issues across the stack.
• Collaborate with cross-functional teams to ensure seamless integration of frontend and backend components.
• Explain technical concepts and analysis implications clearly to various stakeholders and be able to translate business objectives into actionable analysis.
• Stay updated with the latest technologies, frameworks, and industry trends relevant to software development, IoT and high tech.

Requirements:

• 3-5 years of experience in software development with .NET technologies, including C#.
• Strong proficiency in JavaScript and TypeScript.
• Experience in designing and developing IoT applications and services, with exposure to Full Stack development.
• Knowledge of Test-Driven Development (TDD) and Behavior-Driven Development (BDD) methodologies.
• Familiarity with automated testing frameworks and tools.
• Experience with source control systems (GitHub, DevOps etc.).
• Solid understanding of object-oriented programming and software design patterns.
• Proficiency in troubleshooting and debugging applications.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
• Strong problem-solving skills with an attention to detail.
• Proactive attitude and willingness to learn and adapt to different client environments and emerging technologies.

Beneficial Skills and Qualifications:

• Bachelor’s Degree in Computer Science or a field (beneficial).
• Experience with Azure DevOps CI/CD pipelines or GitHub Actions for continuous integration and deployment.
• Familiarity with Azure services such as Azure App Service, Azure Logic Apps Custom Connectors, Azure IoT, and Azure Event Hubs (or equivalent AWS Services).
• Knowledge of frontend frameworks such as Nuxt/Vue, Next/React, or Angular.
• Exposure to agile software development methodologies.
• Experience of containerization using tools like Docker and orchestration tools like Kubernetes.
• Experience with NoSQL databases such as MongoDB or Cosmos DB.
• Exposure and/or hands-on experience in IoT and related technologies.
• Azure or AWS certifications.

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Your day at NTT DATA

• The Principal AI Technology & Innovation Specialist is a highly skilled subject matter expert with deep expertise in emerging AI technologies, advanced analytics, and AI system architecture. This role is accountable for the strategic assessment, experimentation, and enablement of cutting-edge AI solutions within the organization, driving innovation and ensuring AI readiness across internal platforms and client-facing services.
• The primary objective of this role is to stay at the forefront of AI innovation by evaluating, piloting, and recommending next-generation AI technologies and vendor capabilities. The specialist serves as a strategic advisor and hands-on innovator, influencing architecture, engineering, and product teams to integrate AI capabilities in scalable and responsible ways. This includes defining technical blueprints, building AI proof-of-concepts, and supporting adoption through alignment with IT and enterprise architecture.

Key Responsibilities

• Lead the evaluation and strategic assessment of emerging AI technologies, platforms, and vendor solutions, advising on technical and ethical feasibility.
• Design and guide the development of AI capabilities and innovation pilots, translating business goals into AI-enabled solutions.
• Define architectural blueprints for integrating AI technologies into IT systems and product platforms, ensuring security, scalability, and alignment with enterprise standards.
• Develop frameworks for responsible AI adoption including model evaluation, explainability, privacy, compliance (e.g., EU AI Act), and ethical use.
• Partner with product and platform teams to align AI innovations with enterprise technology strategy and business outcomes.
• Drive initiatives for AI prototyping, proof-of-concepts (PoCs), and production readiness assessments.
• Monitor vendor roadmaps and contribute to the strategy for selecting and onboarding external AI capabilities.
• Act as a center of excellence for AI within the IT organization, driving awareness, knowledge sharing, and standardization.
• Collaborate with enterprise architects and platform leads to integrate AI tools into data infrastructure, software architecture, and cloud environments.
• Perform technical due diligence on third-party AI services and models, ensuring fit-for-purpose and cost-effective solutions.
• Continuously improve internal innovation processes and methodologies to increase the speed and quality of AI-driven transformation.

Knowledge and Attributes

• Deep knowledge of modern AI paradigms including generative AI (e.g., LLMs), machine learning infrastructure, AI model lifecycle, and MLOps.
• Strong understanding of AI model risks and evaluation techniques, with experience applying responsible AI principles in enterprise environments.
• Excellent ability to assess multi-vendor and open-source AI offerings for enterprise adoption.
• Advanced knowledge of reference AI architectures, integration models, and cloud-based AI toolchains.
• Ability to translate business needs into technical AI strategies, architectures, and implementation roadmaps.
• Excellent communication and stakeholder management skills across technical, executive, and vendor audiences.
• Strategic thinker with the ability to rapidly assess the value and risks of new AI technologies and innovation trends.

Academic Qualifications and Certifications

• Bachelor’s degree or equivalent in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Advanced degrees (MSc/PhD) in AI/ML fields preferred.
• TOGAF, COBIT, or related enterprise architecture certifications are beneficial.
• Certifications in machine learning or cloud-based AI platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud AI Engineer) are advantageous.

Required Experience

• Extensive experience in leading enterprise AI innovation and architecture initiatives.
• Proven track record of evaluating, piloting, and operationalizing AI solutions in enterprise environments.
• Experience working across multiple industries and large-scale IT organizations.
• Hands-on experience in AI/ML development, integration, and lifecycle management.
• Familiarity with regulations governing AI use, such as the EU AI Act, and experience in operationalizing compliance measures.

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Your day at NTT DATA

• The AI Innovation Engineer is responsible for defining and delivering AI technology solutions that meet enterprise capability requirements. This role focuses on evaluating, designing, and implementing AI solutions from established vendors, ensuring integration with existing enterprise architecture while providing expert guidance on AI technology adoption and innovation strategies.

Key Responsibilities

• Defines AI solutions and technology implementations to deliver specific capability maturity levels for enterprise AI adoption.
• Ensures that AI solutions are agile, scalable, and can be integrated into the overall enterprise architecture and technology landscape.
• Provides expert multi-vendor AI technology advice to internal clients, analyzing and providing strategies and solutions on AI platforms, tools, and integration components.
• Designs and communicates high-level AI solution architectures to enable and guide the implementation of integrated AI capabilities that meet current and future business needs.
• Uses client business requirements to advise on the design, deployment, and operation of AI technology infrastructures and vendor solutions.
• Creates AI solution designs that provide holistic views while containing detailed specifications of AI components and interconnections between systems.
• Involved with AI projects at inception, working alongside project managers in planning and governance of AI initiatives and functional analysis of developing initial AI requirements.
• Works with enterprise architects to define how proposed AI solution components fit into enterprise data architecture, defining clear AI technology roadmaps that improve existing solutions through new AI technologies and methodologies.
• Supports and manages proof of concept (POC) and prototype initiatives to validate new AI solutions, vendor tools, and implementation methods.
• Contributes to improvement of internal effectiveness by enhancing current AI evaluation methodologies, testing processes, and vendor assessment tools.
• Supports internal teams and vendors with installation and configuration of AI applications and platforms.
• Conducts comprehensive vendor AI technology assessments, benchmarking, and capability evaluations.
• Develops and maintains AI testing frameworks and automated evaluation pipelines for continuous vendor solution assessment.
• Establishes AI governance frameworks and best practices for enterprise AI adoption and risk management.
• Performs any other related tasks as required.

Knowledge and Attributes

• Seasoned ability to construct AI solutions using expertise across multiple vendor AI platform offerings and enterprise integration patterns.
• Seasoned knowledge of multi-vendor AI technologies, platforms, and infrastructure design best practices across cloud, hybrid, and on-premises environments.
• Seasoned multi-layered knowledge of AI solution architectures, vendor ecosystems, and enterprise AI reference architectures.
• Seasoned knowledge of project management principles and agile methodologies for AI implementation projects.
• Seasoned knowledge of AI vendor roadmaps, emerging AI developments, and new AI product offerings from major technology providers.
• Deep understanding of AI testing methodologies, performance benchmarking, and capability assessment frameworks.
• Expert knowledge of enterprise AI integration patterns, API management, and AI solution deployment strategies.
• Comprehensive understanding of AI governance, ethics, compliance requirements, and responsible AI practices.
• Analytical in their approach to AI technology evaluation and solution design.
• Excellent interpersonal and communication skills to effectively interact with a variety of stakeholders including vendors, business leaders, and technical teams.
• Ability to share and communicate AI technology concepts clearly, both orally and in writing, to senior management, business sponsors, and technical resources in clear, concise language.
• Displays good business acumen with ability to translate AI technical capabilities into business value propositions.
• Strong vendor relationship management and negotiation skills for AI technology partnerships.

Academic Qualifications and Certifications

• Bachelor's degree or equivalent in Computer Science, Information Technology, Engineering, or related technical field.
• TOGAF / COBIT or related enterprise architecture certification preferred.
• Cloud platform certifications (Azure Solutions Architect, AWS Solutions Architect, or Google Cloud Architect) beneficial.
• AI/ML certifications from major vendors (Microsoft AI Engineer, AWS Machine Learning, Google ML Engineer) preferred.

Required Experience

• Seasoned experience gained in multiple industries and across several AI technology disciplines and vendor platforms.
• Seasoned experience with AI solution development processes, vendor evaluation methodologies, and AI project implementation life cycles.
• Seasoned experience working as a solution architect or senior engineer in enterprise technology environments, with specific focus on AI/ML or similar technologies.
• Proven experience in vendor management, technology assessment, and enterprise AI solution delivery.
• Demonstrated experience in leading complex AI technology evaluations and implementation projects.
• Experience with enterprise AI governance, risk management, and compliance frameworks.
• Track record of successful AI vendor partnership development and management.
• Experience in mentoring junior engineers and contributing to technical team development.