NTT DATA
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a AI Native Product Architect to join our team in Plano, Texas (US-TX), United States (US).
Job Description: AI Native Product Architect
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. Key Responsibilities
Architecture & Solution Design: 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. Hands-On Technical Execution: 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. Technology Evaluation & Integration: 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. Collaboration & Leadership: 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. Required Qualifications
Education: 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. 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. Preferred Skills
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 NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click
here . If you'd like more information on your EEO rights under the law, please click
here . For Pay Transparency information, please click
here .
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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. Key Responsibilities
Architecture & Solution Design: 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. Hands-On Technical Execution: 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. Technology Evaluation & Integration: 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. Collaboration & Leadership: 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. Required Qualifications
Education: 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. 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. Preferred Skills
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 NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click
here . If you'd like more information on your EEO rights under the law, please click
here . For Pay Transparency information, please click
here .
#J-18808-Ljbffr