AI Solution Architect / FDE (AWS and Azure) -

Req ID: 391925 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. We are currently seeking a AI Solution Architect / FDE (AWS and Azure) - to join our team in Toronto, Ontario (CA-ON), Canada (CA). AI Lead / AI Solutions Architect Experience 10+ years software engineering / technology experience | 3+ years hands-on AI/ML Focus AI/ML Architecture | Generative AI | RAG | Multi-Agent Systems | Production AI Industry Financial Services / Regulated Industries preferred About The Role We are seeking an experienced AI Lead / AI Solutions Architect to lead the design, development, and implementation of enterprise AI solutions across Financial Services. This role combines AI/ML engineering, solution architecture, technical leadership, and strategic problem-solving. The ideal candidate will be able to take AI concepts from research and experimentation through architecture, development, deployment, and production—while translating complex technology into measurable business value. You will work closely with data scientists, ML engineers, software developers, product teams, and business stakeholders to deliver scalable AI solutions across areas such as document intelligence, intelligent automation, decisioning, and Generative AI. Responsibilities AI & Solution Architecture • Architect end-to-end AI/ML solutions from concept and experimentation through production deployment. • Design scalable architectures for AI-powered applications, APIs, data pipelines, and intelligent workflows. • Evaluate emerging AI technologies and determine how they can be applied to real-world business challenges. • Lead technical decisions involving Generative AI, RAG, LLMs, multi-agent systems, NLP, and transformer-based models. • Establish standards and best practices for building secure, reliable, scalable, and maintainable AI solutions. • Balance technical innovation with business requirements, scalability, performance, security, and cost. AI/ML Engineering • Lead the development and implementation of production-grade AI/ML solutions. • Develop and evaluate machine learning models and AI applications using modern frameworks and techniques. • Design and optimize RAG pipelines, LLM applications, prompt strategies, and multi-agent architectures. • Work with document intelligence, PDF processing, text extraction, NLP, and automated decisioning use cases. • Develop APIs and services that integrate AI capabilities into enterprise applications. • Establish model evaluation, monitoring, performance measurement, and continuous improvement processes. Technical Leadership & Delivery • Lead complex AI initiatives from discovery and prototyping through production. • Own solution architecture, technical design, implementation strategy, and delivery planning. • Coordinate teams across AI/ML engineering, software development, data science, infrastructure, and business functions. • Translate business requirements into technical solutions, architecture, and implementation roadmaps. • Identify technical risks, dependencies, and opportunities early in the development lifecycle. • Ensure successful transition from experimentation and proof-of-concept to scalable production solutions. AI Platform, DevOps & MLOps • Design and maintain deployment pipelines for AI/ML applications and models. • Establish practices for model deployment, monitoring, versioning, testing, and lifecycle management. • Support integration of AI solutions with enterprise systems, APIs, databases, and data platforms. • Promote automation and repeatable engineering practices across the AI development lifecycle. • Help establish standards for production readiness, observability, reliability, and governance. Technical Mentorship • Mentor engineers and technical team members in AI/ML engineering and software development practices. • Provide guidance on model selection, evaluation techniques, architecture, and implementation approaches. • Conduct code and architecture reviews and promote engineering best practices. • Encourage experimentation, knowledge sharing, technical documentation, and continuous learning. • Help bridge the gap between advanced AI concepts and practical enterprise applications. Required Qualifications • 10+ years of professional software engineering, technology, or relevant research experience. • 3+ years of hands-on AI/ML engineering experience in production environments. • Expert-level Python development skills. • Strong experience designing and implementing end-to-end AI/ML solutions. • Experience with modern AI/ML frameworks such as: • PyTorch • TensorFlow / Keras • Hugging Face Transformers • LangChain or comparable LLM frameworks Strong understanding of Generative AI, LLMs, RAG, NLP, and transformer architectures. Experience designing and developing production APIs and services using technologies such as FastAPI, Flask, or Django. Strong knowledge of RESTful API design and system integration. Experience with SQL and relational databases, including PostgreSQL. Experience developing data processing and ETL pipelines. Proven experience leading complex technical initiatives and working across multiple teams. Strong communication skills with the ability to explain complex technical concepts to both technical and business audiences. Preferred Qualifications • Experience designing and implementing multi-agent AI systems. • Experience with prompt engineering, LLM optimization, and AI evaluation frameworks. • Experience with document intelligence, PDF parsing, OCR, text extraction, or intelligent document processing. • Experience deploying AI solutions in financial services or other highly regulated industries. • Experience with enterprise AI governance, security, responsible AI, and model risk considerations. • Experience with cloud-based AI/ML platforms and modern MLOps practices. • Full-stack development experience, including JavaScript and modern web technologies. • Experience integrating AI solutions with enterprise applications and data platforms. • Published research, technical papers, patents, conference presentations, or other contributions to the AI/ML community. Key Competencies • Strategic thinker who can connect AI capabilities to measurable business outcomes. • Strong problem solver who can navigate complex technical and business challenges. • Hands-on technical leader who can architect solutions and contribute to implementation. • Collaborative communicator who can work effectively with engineers, data scientists, business leaders, and executives. • Innovation mindset with a practical approach to evaluating and adopting emerging AI technologies. • Mentor and team builder who develops technical talent and promotes engineering excellence. • Business focused with an understanding of scalability, ROI, risk, security, and operational impact. Why This Role This is an opportunity to help shape the next generation of enterprise AI solutions within one of Canada's leading financial institutions. You will have the opportunity to work on challenging AI problems, influence architecture and technology strategy, lead highly skilled technical teams, and take emerging AI capabilities from innovation and experimentation to production at enterprise scale. If you are an experienced AI/ML leader who combines deep technical expertise with strong architecture and leadership skills, we'd like to hear from you. Pay Transparency Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this remote role is $163,697-$252,175. 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. This position is eligible for com