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NTT DATA Logo NTT DATA · IT - Software Development

AI Native Product Architect

United States, Dallas 149500.00 - 345800.00 USD / Year · Job Posted January 26, 2026
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Job Description

The AI Native Product Architect role at NTT DATA involves designing and implementing AI-native product architectures. Candidates should have strong technical expertise in AI/ML frameworks, data engineering, and cloud-native systems. Responsibilities include defining technical architecture, building prototypes, and collaborating with product managers and engineers.

Job Responsibility

  • Define and own the technical architecture of AI-native products, ensuring high availability, performance, and security
  • Architect scalable data pipelines, model training, inference services, and orchestration frameworks
  • Design cloud-native, containerized architectures (Kubernetes, microservices, serverless functions) optimized for AI workloads
  • Create reference architectures and reusable design patterns for AI-first product development
  • Build PoCs, prototypes, and reference implementations to validate architecture decisions
  • Develop and optimize APIs, vector databases, and real-time inference pipelines for LLMs and ML models
  • Implement MLOps pipelines for continuous integration, delivery, monitoring, and retraining of models
  • Ensure observability with logging, monitoring, and tracing for data and AI services
  • Evaluate AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, Ray, MLflow) for product suitability
  • Select and integrate data platforms, feature stores, vector DBs (Pinecone, Weaviate, FAISS, Milvus, etc.)
  • Work with cloud AI services (AWS Sagemaker, Azure AI, GCP Vertex AI) and open-source alternatives
  • Optimize cost, latency, and scalability for inference at production scale
  • Work closely with product managers, AI researchers, and engineers to translate requirements into architecture
  • Conduct technical deep-dives, architecture reviews, and performance benchmarking
  • Mentor engineers on AI-native design principles and best practices

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
  • 8+ years in software architecture/engineering, with 4+ years in AI/ML-focused product development
  • Proven hands-on experience in designing and deploying AI-native systems in production
  • Strong proficiency in Python, Java, or Go, with hands-on coding ability
  • Deep knowledge of AI/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain)
  • Experience with data engineering, ETL pipelines, and streaming platforms (Kafka, Spark, Flink)
  • Strong understanding of cloud-native systems (Kubernetes, Docker, microservices)
  • Practical knowledge of vector search, embeddings, retrieval-augmented generation (RAG)
  • Strong grasp of security, governance, and compliance in AI workloads

Nice to have

  • Experience scaling LLM-powered applications with low-latency serving and caching strategies
  • Knowledge of distributed training/inference using GPUs/TPUs, model sharding, and parallelization
  • Familiarity with responsible AI practices: fairness, explainability, auditability
  • Exposure to API design and monetization strategies for AI-powered SaaS products

What we offer

  • medical, dental, and vision insurance
  • flexible spending or health savings account
  • life and AD&D insurance
  • short and long term disability coverage
  • paid time off
  • employee assistance
  • participation in a 401k program with company match
  • additional voluntary or legally-required benefits
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