Ai solutions architect

Department: AI Strategy & Implementation  Reports To: Chief AI Officer / Lead AI Solutions Architect  Travel: International travel required   Position Summary:   We are seeking an AI Solutions Architect with over 20 years of experience to serve as a strategic and technical leader in the design, implementation, and evolution of enterprise-grade AI systems. This role combines architectural vision, hands-on expertise, and executive-level collaboration to ensure AI technologies are not only cutting-edge but also deeply aligned with business outcomes.  The ideal candidate is both a visionary and a practitioner , capable of designing scalable AI architectures from the ground up while guiding cross-functional teams across multiple geographies. This role requires deep proficiency in cloud-native AI infrastructure, data engineering, and machine learning, as well as a strong grasp of governance, compliance, and risk frameworks in high-impact environments.   Key Responsibilities:   Strategic Vision & Road mapping   Define and evolve the long-term AI architecture strategy in alignment with business objectives and industry trends.  Develop technology roadmaps for AI capability development, ensuring scalability, sustainability, and adaptability.  Serve as an AI thought leader across internal and external stakeholders, influencing organizational direction and client strategy.  Architectural Leadership   Lead the design and oversight of end-to-end AI system architectures, including data ingestion, model training, orchestration, deployment, and monitoring.  Integrate ML, NLP, Computer Vision, Deep Learning, and Reinforcement Learning models into scalable production environments.  Balance performance, reliability, security, and cost-efficiency in system design, ensuring real-time and batch AI capabilities.   Cloud & Data Infrastructure   Architect cloud-native infrastructure leveraging AWS, Azure, or GCP, using services such as Sage Maker, Azure ML, Big Query, Redshift, and Kubernetes.  Design robust, secure data pipelines (ETL/ELT) that meet the demanding requirements of AI workloads.  Ensure system integrity, fault tolerance, and business continuity across distributed architectures.  Cross-Functional & Executive Collaboration   Act as a bridge between technical teams and executive leadership, translating strategic vision into actionable architecture.  Engage directly with clients, product leaders, and domain experts to define solution requirements and ensure alignment with organizational objectives.  Lead architectural reviews, capability assessments, and technical workshops with stakeholders across regions.  Leadership & Mentorship   Mentor and guide cross-functional teams, including Data Scientists, ML Engineers, Data Engineers, and Solution Architects.  Establish engineering best practices, architectural standards, and governance frameworks across projects.  Build internal capacity through training, knowledge sharing, and community-of-practice leadership.  Governance, Risk & Compliance   Develop and enforce AI governance, including ethical AI guidelines, bias mitigation strategies, and model explainability standards.  Ensure compliance with global data privacy regulations such as GDPR, CCPA, and regional data sovereignty laws.  Identify and manage technical and operational risks across the AI solution lifecycle.  Global Engagement & Delivery   Travel internationally to lead architectural engagements, support regional solution delivery, and advise clients on AI system implementation.  Support pre-sales and client-facing activities by providing architectural blueprints, technical proposals, and solution prototypes.   Required Qualifications:  Education:   Master’s or Ph. D. in Computer Science, AI, Machine Learning, or a related field is highly preferred.  Bachelor's degree with exceptional industry experience and certifications may be considered. Experience:  20+ years of progressive experience in software engineering, data architecture, and AI system design.  Minimum 10 years in AI/ML-specific architecture, with demonstrated leadership in enterprise or mission-critical environments.  Proven track record of delivering large-scale AI solutions across multiple industries (e.g., government, finance, energy, healthcare). Technical Proficiency:   Machine Learning/AI : Deep expertise in ML frameworks (Tensor Flow, Py Torch), advanced analytics, NLP, Computer Vision, and MLOps.  Cloud Platforms : Expert-level knowledge of AWS, Azure, or GCP, including AI/ML Paa S services.  Data Engineering : Strong command of data pipelines, real-time processing, and orchestration tools (Apache Airflow, Kafka, Spark).  Infrastructure & Dev Ops : Skilled in containerization (Docker, Kubernetes) and automated CI/CD pipelines.  Architecture & Security : In-depth understanding of microservices, distributed systems, API management, and data security protocols. Leadership & Communication:   Outstanding strategic thinking, problem-solving, and communication skills.  Ability to articulate complex technical concepts to executives, business users, and technical teams alike.  Experience influencing cross-functional teams and managing multi-region AI initiatives.   Preferred Certifications:   AWS Certified Machine Learning – Specialty  Azure AI Engineer Associate  TOGAF or similar enterprise architecture certification  PMP, SAFe, or Agile delivery methodologies  Company Description Generative AI solutions are reshaping how we work, and AI Agents are the future. Data-Hat AI assists Enterprises in navigating the AI landscape and building profitable and scalable Enterprise AI solutions. As transformation leaders implore the AI landscape, they seek experts to assist in developing solutions and building strategies. And that’s where Data-Hat AI comes in Guided by an industry veteran, Kshitij Kumar (KK), who has over 2 decades of experience in introducing and implementing Data and AI solutions in Large Enterprises in the US, UK and Europe; a global team of AI and ML experts design Enterprise level AI, Gen AI and AI Agent solutions. We go beyond product development, we collaborate with stakeholders and technology leaders to build a Data and AI strategy, develop a Minimal Viable Product (MVP) and establish ROI. We help Enterprises with impactful AI solutions development.