AI Native Product Architect

NTT DATA • Plano, TX

1d

About The Position

We are currently seeking a AI Native Product Architect to join our team in Plano, Texas (US-TX), United States (US). Role Summary We are looking for a highly skilled AI Product Native Architect to design and implement end-to-end AI-native product architectures. This role demands strong technical expertise in AI/ML frameworks, data engineering, cloud-native systems, and scalable distributed architecture, with hands-on experience building and deploying AI-powered products. The ideal candidate is a practitioner-architect who can move seamlessly from designing high-level architecture to rolling up their sleeves and prototyping solutions.

Requirements

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• Experience: 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.
• Technical Expertise:
• 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 Haves

• 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

Responsibilities

• 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.

Benefits

• This position is eligible for company benefits that will depend on the nature of the role offered.
• Company benefits may include 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, and additional voluntary or legally-required benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees