Generative AI Solutions Architect

nttlimited; United States; On-site; USD 150,000 - 210,000; Full time

Job summary

NTT DATA seeks a Generative AI Solutions Architect to design, develop, and support GenAI-enabled applications and workflows across the GIN division. You will evaluate models, plan deployments, and ensure secure, scalable adoption with cross-functional teams.

You will collaborate with software, infrastructure, platform, security, and operations teams to translate use cases into practical technical solutions and maintain reference designs and procedures for GenAI initiatives.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or related field or equivalent practical experience.
• Working knowledge of Python, APIs, source control, testing, containers, and automated deployment.
• Knowledge of GPU compute and memory, foundation-model capabilities, and open-source or hosted model platforms including Ollama and Qwen.

Responsibilities

• Design, develop, test, deploy, and maintain GenAI-enabled applications, services, and reusable components.
• Evaluate and select foundation models and deployment approaches based on quality, latency, cost, security, privacy, and fit.
• Design and integrate model-driven workflows with testing, guardrails, and fallback behavior.
• Provide input on feasibility, architecture, data needs, GPU capacity, security, and responsible AI considerations.
• Create and maintain reference designs, documentation, and guidance for GenAI solutions.

Skills

GenAI architecture

Python

Cloud platforms

Stakeholder comms

Education

Bachelor's degree in CS/SE

Tools

Ollama

Qwen

Job description

Make an impact with NTT DATA

Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion - it's a place where you can grow, belong and thrive.

The Generative AI Solutions Architect designs, develops, and supports AI-enabled applications, workflows, and reusable capabilities while helping teams evaluate and implement AI solutions effectively. This role blends software engineering, AI architecture, and stakeholder consulting to drive secure, scalable, and sustainable AI adoption across the GIN organization.

Want to be a part of our team?

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.

Key Responsibilities

• 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.

Education / Qualifications required

• 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 .

Organizational Relationships

Reports directly to the Executive Head, SAS

Works closely with software engineering, infrastructure, platform, security, and operations teams.