Generative AI Solutions Architect

• Design, develop, test, deploy, and maintain GenAI-enabled applications, services, APIs, and reusable components for internal platforms and project teams.
• Evaluate and select foundation models and deployment approaches, including open-source and locally hosted models such as Qwen and Ollama-based deployments, using quality, latency, cost, security, privacy, and platform-fit criteria.
• Design and integrate model-driven workflows such as prompting, retrieval-augmented generation (RAG), tool use, and agentic patterns, with appropriate testing, evaluation, guardrails, and fallback behavior.
• Provide early technical input to project teams on feasibility, architecture, model selection, data requirements, GPU capacity, security, responsible AI considerations, performance, and operational risks.
• Create and maintain reference designs, technical documentation, evaluation methods, operating procedures, standards, observability guidance, and recommended usage patterns for GenAI solutions.
• Partner with software, infrastructure, platform, security, and operations teams; educate technical and non-technical stakeholders on GenAI capabilities and limitations; and provide actionable feedback to the Executive, Head - SAS on platform gaps and improvement priorities.
• Develop and maintain reporting at established intervals on significant GIN AI initiatives, activities, and project outcomes. Maintain current GIN AI documentation and guidance, including recommended AI models, core tools, platforms, and other resources available to GIN staff, updating content as organizational needs, technologies, and standards evolve., * Reports directly to the Executive Head, SAS
• Works closely with software engineering, infrastructure, platform, security, and operations teams.
• Engages with technical leadership, project teams, and non-technical stakeholders on a project basis.

Success Measures :

• Delivery of reliable, supportable GenAI tools, services, or reference implementations that meet defined acceptance criteria and are adopted by project teams.
• Build and maintain clear and current documentation, standards, and operating guidance that support consistent implementation and support practices.
• Early identification of GenAI design issues, security or responsible AI risk, resource constraints, and operational gaps with actionable recommendation that improve AI platform readiness.
• Demonstrable improvements in solution quality, latency, cost, reliability, or supportability through effective evaluation, architecture, and operational practices.

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field; or equivalent practical experience.
• Working knowledge of software engineering practices relevant to GenAI solutions, including Python or comparable programming, APIs, source control, testing, containers, and automated deployment practices.
• Working knowledge of GPU compute and memory considerations, foundation-model capabilities and limitations, and open-source or locally hosted model platforms, including tools such as Ollama and models such as Qwen.

Work Experience Required:

• Demonstrated experience designing, building, and supporting GenAI-enabled applications, services, or internal tools in an enterprise or applied engineering environment.
• Demonstrated experience working across software engineering, infrastructure, architecture, security, operations, and business stakeholders to translate use cases into practical technical solutions.
• Demonstrated experience developing and integrating model-driven workflows, including prompting, inference patterns, testing, evaluation, and support practices.
• Demonstrated experience creating technical documentation, implementation guidance, or standards for both technical and non-technical audiences.
• Demonstrated experience working in network services, telecommunications, managed services, or similar infrastructure-based companies.

Skills and Core Competencies:

• Ability to assess technical tradeoffs involving solution quality, cost, latency, performance, scalability, maintainability, security, privacy, and operational fit.
• Strong written and verbal communication skills, including the ability to explain complex GenAI concepts, risks, and recommendations clearly to mixed audiences.
• Strong analytical and experimental approach to model and workflow evaluation, including defining acceptance criteria and interpreting evaluation results.
• Ability to work independently and across project teams, exercise sound technical judgment, identify risks early, and recommend approaches that can be supported at scale .

NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this remote role is 92K-131K. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.

This position may also be eligible for incentive compensation based on individual and/or company performance.

This is a role in our Global IP Network (GIN) division. NTT and the Global IP Network have been recognized as the Best Global Wholesale Carrier (Data) 2021 at the Global Carrier Awards. Our Tier-1 Global IP Network, consistently ranked among the top networks worldwide, spans the Americas, Europe, Asia and Oceania, operating under a single AS 2914., About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune

Global 100. We are committed to accelerating client success and positively impacting society through

responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with

unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and

application services. Our consulting and industry solutions help organizations and society move

confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more

than 70 countries. We also offer clients access to a robust ecosystem of innovation centers as well as

established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each