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The Senior AI Solution Architect is a senior technical subject matter expert responsible for architecting, developing, deploying, and continuously evolving production-grade AI products and intelligent services that accelerate business innovation, operational excellence, and digital transformation. This role spans the complete AI, product, and service lifecycle—from opportunity identification, business case development, solution architecture, data strategy, model development, validation, deployment, operations, optimization, and continuous improvement—across cloud, edge, IoT, robotics, and embodied AI environments.

The successful candidate will transform cutting-edge IIoT, AI research into secure, scalable, commercially viable, and enterprise-ready solutions while ensuring alignment with business objectives, enterprise architecture, cybersecurity, governance, operational excellence, and client experience. They will serve as a technical leader, partnering with product management, engineering, research, operations, enterprise architecture, and executive stakeholders to define AI strategy, accelerate time-to-market, and establish best practices for production AI systems.

This role requires deep expertise in modern Foundation Models, Large Language Models (LLMs), Vision-Language Models (VLMs), Computer Vision, Agentic AI, Physical AI, Robotics, Multimodal Intelligence, and Liquid Foundation Models (LFMs). The engineer will build intelligent systems that bridge AI with enterprise software, industrial automation, IoT platforms, sensors, robots, digital twins, and autonomous systems operating under real-world latency, safety, reliability, and resource constraints.

Key Responsibilities

AI Strategy, Product & Service Development

Lead the complete lifecycle of AI products and intelligent services from concept through production and continuous optimization.

Translate business, operational, industrial, and robotics challenges into scalable AI-powered products and services.

Develop business cases, value propositions, technical roadmaps, and commercialization strategies for new AI capabilities.

Coordinate cross-functional engineering activities to deliver AI solutions on schedule, within budget, and aligned with enterprise development methodologies.

Ensure AI initiatives align with enterprise architecture, cybersecurity standards, governance frameworks, operational requirements, and strategic business priorities.

Drive continuous improvement of AI engineering methodologies, development standards, and service delivery practices.

Conduct post-deployment reviews and identify opportunities for optimization, automation, monetization, and operational improvements.

AI Research, Engineering & Production

Own the end-to-end AI lifecycle from research and experimentation through production deployment, monitoring, and continuous improvement.

Design robust data acquisition, labeling, curation, governance, validation, and evaluation strategies.

Develop scalable training, fine-tuning, inference, and deployment pipelines.

Establish production-grade MLOps capabilities including experiment tracking, dataset versioning, model registries, CI/CD, observability, drift detection, model governance, and operational monitoring.

Deliver highly available, secure, maintainable, and scalable AI services across cloud, edge, embedded, and hybrid infrastructures.

Foundation Models & Multimodal Intelligence

Design, train, fine-tune, optimize, and deploy state-of-the-art AI systems including:

Foundation Models

Large Language Models (LLMs)

Vision-Language Models (VLMs)

Computer Vision

Multimodal AI

Liquid Foundation Models (LFMs)

Sensor Intelligence

Robotic Perception

Apply advanced expertise in

Transformer architectures

Self-attention and cross-attention

Positional encoding

Representation learning

Scaling laws

Distributed training

Optimization dynamics

Fine-tuning methodologies

Prompt engineering and model evaluation

Agentic AI & Autonomous Systems

Design intelligent AI agents capable of:

Autonomous reasoning

Long-term memory

Planning

Tool utilization

Workflow orchestration

Multi-agent collaboration

Human-in-the-loop interaction

Autonomous execution

Develop enterprise agentic platforms integrating with:

Enterprise applications

APIs

Knowledge bases

Operational systems

Industrial equipment

IoT and IIoT platforms

Robotic systems

Edge devices

Implement governance frameworks covering:

Safety

Security

Explainability

Evaluation

Monitoring

Responsible AI

Compliance

Risk management

Physical AI, Robotics & Autonomous Systems

Develop intelligent robotic systems integrating:

Perception

Localization

Mapping

Planning

Manipulation

Navigation

Motion control

Autonomous reasoning

Closed-loop decision making

Support solutions across

Industrial automation

Manufacturing

Warehousing

Logistics

Autonomous inspection

Smart infrastructure

Human-robot collaboration

Critical infrastructure

Autonomous mobile robots

Integrate modern AI with classical robotics, controls engineering, and safety-critical system design.

Perception, Sensor Fusion & Digital Twins

Design multimodal perception systems utilizing:

RGB cameras

Stereo vision

Depth cameras

LiDAR

Radar

IMUs

Industrial sensors

Telemetry

Time-series data

Develop sensor fusion pipelines supporting:

Scene understanding

SLAM

Localization

Mapping

Object tracking

Anomaly detection

Situational awareness

Predictive intelligence

Decision support

Develop Digital Twin and Sim2Real environments to:

Generate synthetic data

Validate AI behavior

Evaluate safety





Stress-test edge cases

Reduce deployment risk

Accelerate AI training

Efficient AI & Edge Intelligence

Optimize AI models using

Quantization

Distillation

Structured pruning

LoRA

PEFT

Runtime optimization

Compiler optimization

Graph optimization

Hardware-aware optimization

Deploy optimized AI across

Embedded platforms

NVIDIA Jetson

GPUs

NPUs

Industrial edge platforms

Robotics platforms

Resource-constrained IoT devices

Deliver real-time AI systems optimized for latency, throughput, power consumption, memory utilization, and operational cost.

Enterprise AI Architecture, Security & Governance

Apply Secure-by-Design principles throughout the AI lifecycle.

Ensure compliance with enterprise architecture, cybersecurity, privacy, regulatory, and governance standards.

Design AI systems emphasizing resiliency, observability, explainability, traceability, and operational reliability.

Implement AI governance, model lifecycle management, access control, data governance, and responsible AI practices.

Collaborate closely with cybersecurity, enterprise architecture, infrastructure, platform engineering, and operations teams.

Service Design & Client Experience

Develop comprehensive business, technical, operational, and architectural documentation throughout the AI lifecycle.

Produce service definitions, solution architectures, deployment guides, operational runbooks, and support documentation.

Design AI services that maximize client value, operational efficiency, adoption, and commercial outcomes.

Ensure solutions are operationally supportable, maintainable, scalable, and aligned with enterprise service management practices.

Stakeholder Leadership

Partner with executive leadership, product management, research, engineering, operations, enterprise architecture, and customers.

Communicate complex AI concepts to both technical and non-technical stakeholders.

Provide executive dashboards, technical assessments, and strategic recommendations.

Mentor engineers and establish engineering standards, best practices, and technical roadmaps.

Influence enterprise AI strategy and drive innovation across the organization.

Knowledge & Competencies The successful candidate demonstrates:

Expert knowledge of Artificial Intelligence, Machine Learning, Deep Learning, Foundation Models, and modern transformer architectures.

Strong understanding of enterprise software architecture, cloud-native systems, distributed computing, edge computing, IoT, robotics, and autonomous systems.

Advanced knowledge of AI product lifecycle management, MLOps, production AI operations, and service engineering.

Strong commercial awareness with the ability to translate technical innovation into measurable business value.

Excellent analytical, documentation, research, communication, and stakeholder management skills.

Proven ability to influence technical direction across multidisciplinary teams.

Strong customer focus with an emphasis on operational excellence and continuous innovation.

Required Qualifications

Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Computer Engineering, Electrical Engineering, or a related discipline. A Ph.D. is considered an asset.

Extensive experience developing and deploying production-grade AI systems using Python, PyTorch, CUDA, distributed training frameworks, and modern MLOps practices.

Demonstrated expertise in Foundation Models, LLMs, VLMs, Computer Vision, Multimodal AI, Agentic AI, and Physical AI.

Strong experience with robotics frameworks such as ROS/ROS 2, NVIDIA Cosmos, Omniverse, Isaac Sim, Isaac Lab, Gazebo, MuJoCo, MoveIt, or equivalent simulation and Digital Twin platforms.

Experience optimizing AI models for edge deployment using TensorRT, ONNX Runtime, quantization, pruning, distillation, and hardware-aware optimization.

Proven experience deploying AI solutions across cloud, edge, embedded, robotics, and industrial IoT environments.

Preferred Qualifications

Experience with embodied AI, world models, synthetic data generation, and simulation-driven AI development.

Experience in industrial automation, manufacturing, logistics, transportation, aerospace, energy, utilities, healthcare, or other mission-critical industries.

Experience deploying AI solutions in safety-critical or regulated environments.

Contributions to open-source AI, robotics, or multimodal learning communities.

Publications, patents, or recognized innovation in AI, robotics, or autonomous systems.

Professional certifications in Agile, ITIL, Kubernetes, AWS, Azure, Google Cloud, NVIDIA, or related technologies.

The ideal candidate combines the capabilities of an AI researcher, machine learning engineer, robotics engineer, software architect, systems engineer, product strategist, and technical leader. They excel at transforming emerging AI research into secure, scalable, production-ready AI platforms that deliver measurable business value while balancing innovation, operational excellence, governance, client experience, and commercial success. They are equally comfortable discussing transformer internals, multimodal reasoning, robotics, edge AI optimization, enterprise architecture, MLOps, and executive AI strategy, while mentoring engineering teams and shaping the organization's long-term AI vision.

Your day at NTT DATA The Senior AI Solution Architect is an advanced subject matter expert, responsible for supporting the organization's strategic goals of service revenue protection and growth, and operating profit improvement.



This role is responsible for increasing the company's ability to consistently and predictably deliver relevant, profitable and high-quality service offers and capabilities.

In this role you will:

Manages the coordination of activities, actions and deliverables in the service development process to ensure completion within time and budget and in line with development standards and methodologies.

Drives and evolves a robust regional inter-lock for service development aligned to the global/group methodology to ensure expedient time-to-market / release of developments.

Ensures new service offer requirements from Service Offer Management have clearly defined business value outcomes, and that requirements are substantiated by an appropriate business case, and prioritized according to business impact and importance.

Where required, supports Service Offer Management in the formation of business cases for new service offers.

Supports the identification, development and implementation of service pre-design in line with agreed technical, operational and architectural specifications.

Throughout the development cycle, prepare and maintain documents for service design/definition relating to the development of new services or enhancements to existing services.

Supports with providing reports and dashboards highlighting risks, issues and trends to support management decision making.

Pays attention to the security architecture, standards and requirements for the new service, ensuring the secure-by-design principle.

Ensures that the client journey is defined, design and implemented, optimizing client experience and maximizing economic return through new monetizable client features and capabilities.

Use expertise to provide input into the continuous improvement of the services development methodology and its practices.

Conduct post implementation reviews to audit the commercial, operational and technical performance of new service offers, and provide feedback to the business on possible improvements and optimization opportunities.

You are perfect for this role if you:

Advanced understanding of the vast range of IT operations and company's service offerings.

Advanced knowledge and understanding of IT industry environment and business needs.

Excellent relationship management and demonstrated collaborative skills in working with internal and external business leaders and stakeholders.

Excellent communication skills (verbal and written) coupled with good questioning skills.

Advanced knowledge of the design / development of procedures and technical features required to fulfil all the elements relevant to the service.

Advanced documentation capabilities, in particular business requirements.

Advanced analytical and research skills.

Advanced ability to persuade, negotiate and influence key stakeholders.

A go-getter with the ability to work in high-pressure situations.

Ability to establish and manage processes and practices through collaboration and the understanding of business.

Service orientated individuals who are able to create client value whilst maintaining profitable business results.

Academic qualifications and certifications:

Bachelor’s degree or equivalent in Information Technology or Computer Science or Business or related field.

Relevant certifications such as Scaled Agile and ITIL are beneficial.

Required experience

Advanced experience working in an Information Technology environment, particularly within IT Operations.

Advanced experience in similar role within a related workplace.

Advanced experience in effective product lifecycle management and service delivery excellence.

NTT DATA provides a reasonable range of compensation for Canada-based positions. The starting pay range for this remote role is 95,000 CAD-145,000 CAD. This range reflects the minimum and maximum target compensation for the position across all Canada locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.

Workplace type: Remote Working

About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services.

Our consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 70 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners.

NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D.;

Equal Opportunity Employer

NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category.

Join our growing global team and accelerate your career with us. Apply today. Third parties fraudulently posing as NTT DATA recruiters NTT DATA recruiters will never ask job seekers or candidates for payment or banking information during the recruitment process, for any reason.

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📌 Senior AI Solution Architect (Toronto)
🏢 NTT
📍 Toronto