Your day at NTT DATA

As a Senior Solutions Architect at NTT DATA, you will play an essential role in collaborating with clients and internal teams to create advanced, transformational designs and architectural visions for complex solutions. Your expertise will drive the development of multi-technology consulting services that span application software, infrastructure, and related technology components.

You will contribute to complex solution architectures in specific business, infrastructure, or functional areas while evaluating alternative architectures for cost, performance, and scalability. By developing detailed specifications for cloud-based or on-premises components, you will ensure robust, cutting-edge solutions that meet our clients' unique needs.

Your hands-on role will involve preparing technical plans and designs that comply with enterprise and solution architecture standards, remaining agile to adapt to changing project requirements. You will be accountable for understanding client requirements, collecting data, delivering thorough analysis, and providing effective problem resolution.

Key Responsibilities

Deal intake and GTM interlock

• Act as the primary technical and delivery interlock for assigned AI opportunities from qualified intake through solution approval, contracting and handover to delivery.
• Engage with regional GTM, sales and solution teams early in the opportunity lifecycle to understand the client’s business problem, intended outcomes, technical environment, data landscape and commercial requirements.
• Assess whether the opportunity is sufficiently qualified for Global AI Delivery engagement and identify any additional information, discovery or customer validation required.
• Review use-case descriptions and business requirements to assess whether the proposed use of AI is appropriate, feasible and aligned with measurable client outcomes.
• Support structured discovery sessions with clients and internal stakeholders, translating business requirements into actionable technical and delivery requirements.
• Identify the specialist capabilities required to support the pursuit and coordinate targeted engagement from Global AI Delivery Unit, security, legal, commercial and regional delivery teams.
• Manage the involvement of delivery specialists carefully, ensuring that delivery expertise is used for material design decisions and specialist validation without drawing delivery teams unnecessarily into general pre-sales activity.
• Maintain clear communication with opportunity owners regarding solution status, outstanding decisions, risks, dependencies and readiness for assurance.

AI solution architecture and design

• Shape or own the end-to-end architecture of AI solutions across application, model, data, integration, infrastructure and security domains.
• Evaluate architecture options and select appropriate AI models, cloud services, orchestration frameworks and third-party technologies, balancing cost, performance, scalability, security and delivery complexity.
• Define secure integration, functional and non-functional requirements, data governance and responsible AI requirements for the proposed solution.
• Align solutions with NTT DATA reference architectures, reusable assets, delivery patterns and approved technology standards.

Commercial solution development

• Work with commercial, finance, sales and delivery stakeholders to develop a commercial construct aligned to the architecture and delivery model.
• Validate estimates, rate-card assumptions, third-party costs, consumption charges and contingency, ensuring all material delivery costs are represented.
• Ensure the resource model, delivery estimate, pricing, contribution and margin assumptions remain internally consistent, with uncertainty managed through appropriate commercial mechanisms.
• Support pricing and approval processes and challenge commercial constructs that create unmanageable technical or delivery risk for NTT DATA.

Scope and statement-of-work development

• Support the drafting and review of proposals and statements of work, defining scope, deliverables, milestones, assumptions, exclusions, dependencies, client responsibilities and acceptance criteria.
• Ensure contractual artefacts accurately reflect the approved architecture, delivery approach, resource plan and commercial model, without ambiguous or unbounded commitments.
• Coordinate legal, security, data protection and responsible AI input and support negotiation of technical and delivery-related contractual terms.

Deal assurance and governance

• Assess the completeness and quality of the proposed solution across architecture, technical feasibility, delivery readiness, resource requirements, commercial consistency and risk treatment.
• Identify material technical, data, security, privacy, legal, commercial and delivery risks and ensure appropriate owners and mitigations are in place.
• Prepare and present assigned opportunities for relevant assurance and approval gates, coordinating required stakeholder review and sign-off.
• Provide a clear, evidence-based assurance recommendation: proceed, proceed subject to conditions, return for rework or do not proceed in the proposed form.
• Track assurance conditions, escalate material concerns and maintain appropriate decision records; ensure independent review where the architect has materially developed the solution.

Delivery planning and resource model

• Translate the solution into a realistic delivery approach covering workstreams, deliverables, milestones, dependencies and mobilisation.
• Define or validate the resource model, effort estimates, skills, location strategy and use of global delivery centres, partners or subcontractors.
• Assess delivery timelines and define appropriate governance, roles, responsibilities, escalation and change control.
• Identify requirements for managed services, production support, model monitoring, platform operations or continuous optimisation where applicable.

Prototyping and feasibility validation

• Develop, lead or coordinate prototypes and proofs of concept where required to validate feasibility, reduce delivery risk or demonstrate the proposed solution.
• Test material assumptions relating to model performance, data, integration, security, scalability, latency and consumption cost, with clear success and exit criteria.
• Translate prototype findings into the production architecture, estimate, assumptions and risk position, engaging specialist engineering support where required

Transition and handover to delivery

• Maintain a controlled solution baseline through contracting and mobilisation, ensuring material changes are reflected consistently across deal artefacts.
• Lead the transition to delivery, providing the approved architecture, scope, commercial baseline, resource plan, assumptions, dependencies, risks and client commitments.
• Support early mobilisation, resolve gaps between what was sold and what is being delivered, and capture feedback to improve future solutioning and estimates.

Reuse and capability development

• Contribute reusable AI architectures, delivery patterns, prototypes, estimation models, proposal assets and commercial assumptions informed by pursuit and delivery experience.
• Share knowledge, coach regional teams and continuously improve the methods, templates and governance controls used by the AI Deal Intake, Assurance & Governance function.

Knowledge and Attributes

• Advanced enterprise solution architecture knowledge across application, integration, data, infrastructure, cloud and security domains.
• Strong understanding of AI, generative AI and agentic AI solution patterns, including model selection and evaluation, RAG, prompting, grounding, data pipelines, APIs and vector databases.
• Strong knowledge of major cloud platforms and their AI, data, integration and security capabilities, with working knowledge of software engineering, DevOps, MLOps and LLMOps.
• Ability to develop or lead prototypes and assess the path from proof of concept to a secure, scalable and supportable production solution.
• Strong understanding of security, privacy, compliance, data governance and responsible AI considerations.
• Commercial acumen across estimates, rate cards, pricing models, third-party costs, contribution, margin, contingency and cost recovery.
• Understanding of statements of work, contractual assumptions, acceptance criteria, client dependencies, change control and delivery transition.
• Strong client-facing consulting, communication and stakeholder-management skills across technical, commercial, delivery and executive audiences.
• Ability to exercise constructive challenge, make evidence-based decisions and manage multiple complex opportunities under demanding pursuit timelines.
• Strong analytical capability and attention to detail when reviewing solution, commercial and contractual artefacts.

Academic Qualifications and Certifications

• Bachelor’s degree or equivalent practical experience in computer science, engineering, data science, information systems, business or a related field.
• Language requirement: business level Japanese language skill (minimum JLPT N2) or native
• Business level English language skill
• Minimum 5 years working experience in enterprise solution architecture, technical consulting, pre-sales and delivery, engaging with senior clients
• Relevant cloud or AI certification from Microsoft Azure, Amazon Web Services or Google Cloud Platform is preferred.
• Enterprise or solution architecture certification such as TOGAF is advantageous; additional AI, security, privacy, agile, project or service-management certifications are beneficial.

Ideal / Desired Experience

• Demonstrated experience designing or validating enterprise AI and generative AI solutions, including prototypes and integration with enterprise platforms and data.
• Experience with one or more major cloud platforms and their AI, data and integration services.
• Experience defining delivery scope, work breakdown structures, resource models, effort estimates and delivery plans.
• Experience contributing to commercial models, pricing assumptions, rate-card constructs or business cases for complex technology engagements.
• Experience drafting or reviewing statements of work, managing technical and delivery risk, and supporting formal solution or deal-assurance reviews.
• Experience transitioning solutions into delivery and working across sales, commercial, engineering, delivery, security, legal and partner teams; regulated environments and AI managed services/MLOps/LLMOps experience are advantageous.

Workplace type:

Equal Opportunity Employer
NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Accelerate your career with us. Apply today