Member of Technical Staff - Engineering I [Bay Area]

NTT DATA AIVista•Palo Alto, CA

7h•Hybrid

About The Position

NTT DATA AIVista, a subsidiary of NTT DATA, specializes in developing AI products that operationalize AI for enterprises in complex regulatory environments. We collaborate with other NTT companies to ensure successful client deployments, combining AIVista's AI product expertise with NTT DATA's industry knowledge and systems integration experience. This role is for engineers with proven experience building and launching AI products in production, not just integrating third-party tools. The Member of Technical Staff will design, develop, and deploy AI capabilities, including agentic infrastructure, model customization, and agentic workflows for large enterprises. The position demands exceptional software engineering skills and hands-on experience with scalable AI systems in production. You will collaborate with engineering, science, product, and customer teams to solve complex business problems in regulated industries. Success requires comfort with the full AI product lifecycle, from design and implementation to deployment, optimization, and production support. This is a hands-on role for engineers who have directly designed, built, launched, and operated AI products and platforms in production, delivering measurable business value and customer impact at scale. Experience building AI platforms, infrastructure, models, agentic systems, or AI-powered products is essential. Candidates focused solely on consuming or integrating third-party AI services without owning the underlying systems are not a good fit.

Requirements

Undergraduate degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent practical experience.
Demonstrated hands-on industry experience delivering complex work independently in the design, building, deploying, and operating production AI systems used by enterprise customers.
Proven experience in the development and launch of AI-powered products, platforms, or capabilities that achieved meaningful customer adoption, business impact, or industry recognition, including experience building scalable, maintainable, and production-ready systems.
Experience building core AI platforms, infrastructure, agentic systems, model customization pipelines, or large-scale AI applications, rather than solely consuming or integrating third-party AI products and services.
Hands-on expertise with modern AI technologies, including at least four of the following: Agentic systems and agent orchestration, Retrieval-Augmented Generation (RAG), Model customization, tuning, and optimization, Large Language Models (LLMs), AI infrastructure and inference systems, Data processing and knowledge pipelines, Agent protocols and multi-agent architectures.
Demonstrated ability to make architectural and implementation decisions that balance performance, scalability, reliability, cost, and customer requirements.
Demonstrated understanding of Natural Language Processing (NLP), modern AI application architectures, and large-scale distributed systems.
Experience deploying and operating AI workloads on cloud platforms.
Strong problem-solving, analytical, communication, and collaboration skills.

Nice To Haves

Master's or PhD degree preferred.
Sound technical judgment that colleagues can rely upon.

Responsibilities

Designing, developing, and deploying AI capabilities, including agentic infrastructure, model customization, and agentic workflows.
Working closely with engineering, science, product, and customer teams to deliver AI capabilities that solve complex business problems within highly regulated industries.
Operating across the full lifecycle of AI product development, from technical design and implementation through deployment, optimization, and production support.
Troubleshooting, optimizing, and operating complex AI systems in production environments.
Translating advanced AI techniques into practical customer-facing solutions.
Mentoring engineers, leading technical discussions, conducting design reviews, or influencing technical direction across teams.