Senior Digital Solution Architect - AI/ML Product Specialist

Digital Solution Architect Sr. Advisor

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.  We are seeking a candidate  specializing in technology division to lead both  business process solutions and IT side of business to join our dynamic team at NTT DATA. As an SME (subject matter expert), you will closely work with NTT DATA’s customers to understand their business problems and engage with them to provide consulting and solutioning for solving their business problems using AI ML and Automation related technologies. Design and implement effective AI technologies and methods to address clients' business problems and needs, while complying with company's strategies, business goals, and key ethical considerations. Your engagement with the customer should give the customer confidence that NTT DATA is the right business and technology partner for their operation.

 

Experience Requirement:

• 10+Experience in solution architecture with an emphasis on business process services
• 7+ Experience in Banking, Financial Services, and Insurance (BFSI) Industry, Healthcare, Manufacturing
• 3+ years of experience with automation and machine learning solutions.
• 5+ Years in financial cost modelling.
• Experience with creating and communicating business value prop to executive in both oral and written format.

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.
• Be a solution architecture/designer for business processes.
• Independently able to solution and respond to RFP’s.
• Ability to clearly articulate value to C level executives of the client
• Provide solution and technology consulting and drive opportunities for leveraging GenAI, AI based solutions on various platforms
• Drive close discussions with client and draw technical and functional requirements through workshops with stakeholders
• Develop Point of Views that provide details of scope, due-diligence, approach and business/cost benefit.
• Collaborate with NTT DATA Global business and stakeholders

Qualifications

• Bachelors / Masters / PhD degree in Computer Science or related field
• Certification or Degree with AI and machine learning.

Skills

• Excellent communication and articulation in English language
• Strong excel and math acumen.
• Excellent problem-solving and analytical skills.
• Enthusiasm for AI/ML technologies and a proactive attitude towards learning and staying updated.

Experience Level

Senior Level