Senior Solution Architect - AI & ML

Job Title: Senior Solution Architect – AI & ML

Role Overview

As a Senior Solution Architect – AI & ML, you will serve as a strategic technology leader responsible for architecting enterprise-scale AI and data solutions that drive innovation, intelligence, and digital transformation. You will lead the design and evolution of advanced data platforms, AI ecosystems, and analytics solutions, while providing architectural guidance, technical leadership, and hands-on support for implementation initiatives, MVP development, and complex problem-solving.

This role will play a pivotal part in shaping the technology foundation of a newly established Global Technology Center (GTC), influencing both immediate project delivery and long-term enterprise technology strategy. The ideal candidate will combine deep technical expertise, architectural vision, and leadership capabilities to build scalable, secure, and future-ready AI-powered systems.

Key Responsibilities

Strategy & Planning

• Define and drive the AI and data architecture vision, roadmap, and strategy aligned with enterprise digital transformation objectives.

• Identify opportunities for AI-driven innovation, automation, and operational excellence across business functions.

• Influence enterprise architecture decisions to ensure AI and data capabilities are integrated into core business platforms.

• Evaluate build-versus-buy decisions, vendor offerings, and open-source technologies to accelerate innovation and business value.

• Establish architecture governance, standards, and best practices across AI and data initiatives.

Delivery & Execution

• Architect and lead the development of enterprise-scale AI and data platforms supporting Gen AI, predictive analytics, intelligent automation, and advanced analytics use cases.

• Design end-to-end solutions leveraging LLMs, RAG pipelines, real-time data processing, and cloud-native services.

• Define scalable architecture patterns and technical standards to ensure performance, maintainability, security, and reliability.

• Lead technical evaluations, architecture reviews, and Proof of Concepts (PoCs) for emerging technologies.

• Collaborate with engineering, product, and data science teams to translate complex business requirements into scalable and robust solutions.

• Drive the implementation of Well-Architected Framework principles across AI and data platforms.

Support & Enablement

• Develop reusable architecture assets, reference architectures, accelerators, and implementation frameworks.

• Provide technical guidance and troubleshooting support for critical AI and data platform challenges.

• Engage with technology partners, vendors, and industry communities to stay current with emerging AI and data trends.

• Champion responsible AI practices, ensuring fairness, transparency, governance, and compliance across AI solutions.

People Leadership

• Mentor and guide solution architects, data engineers, machine learning engineers, and AI specialists.

• Foster a culture of innovation, collaboration, and engineering excellence.

• Support talent development, succession planning, and capability-building initiatives within the technology organization.

• Drive architectural knowledge sharing and technical excellence across teams.

Required Qualifications

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical field.

• Cloud Architecture certification such as Google Cloud Professional Architect or equivalent is preferred.

• Data Engineering certifications such as Google Cloud Data Engineer, Databricks Certified Data Engineer, or equivalent are preferred.

Experience Requirements

• 12–15 years of experience in software engineering and solution architecture.

• Minimum 7–8 years of experience leading AI, ML, and data-intensive programs at enterprise scale.

• Proven experience designing and delivering large-scale, cloud-native AI and data platforms.

• Strong track record in driving enterprise technology strategy, innovation initiatives, and architecture governance.

Essential Skills

• Expert in designing AI/ML systems using TensorFlow, PyTorch, and Hugging Face.

• Strong experience with data engineering technologies including Apache Spark, Kafka, Airflow, and Delta Lake.

• Deep expertise in cloud-native architecture and AI/ML services on AWS, Azure, or GCP.

• Skilled in building scalable APIs, microservices, and event-driven systems.

• Proficient in MLOps and DataOps using MLflow, Kubeflow, and CI/CD pipelines.

• Strong experience evaluating and integrating Generative AI technologies, including LLMs, RAG, and agentic frameworks.

• Excellent stakeholder management, communication, and technical leadership skills.

Desired Skills

• Strong understanding of data governance, security, privacy, and compliance in distributed systems.

• Exposure to multi-agent systems and autonomous AI architectures.

• Familiarity with enterprise data platforms.

• Experience with semantic search, vector databases, and graph technologies.

• Knowledge of AI observability, model monitoring, and responsible AI frameworks.