Senior Solutions Architect

As a highly skilled and visionary Solution Architect specializing in Artificial Intelligence (AI) and Automation, your role will involve leading the design and implementation of cutting-edge solutions in AI, Generative AI, and Automation. You will need to leverage your technical expertise, strategic thinking, and leadership abilities to drive innovation and deliver scalable, high-impact solutions across the organization. Key Responsibilities: - Design end-to-end AI and automation solutions that are aligned with business goals and technical requirements. - Participate in discussions on business requirements and develop solutions and technical architecture that address all aspects of the business problem. - Define architecture blueprints, integration patterns, and data pipelines for AI-driven systems. - Evaluate and select appropriate AI models, automation tools (e.g., RPA, BPM), and cloud platforms. - Ensure scalability, security, and performance of deployed solutions. - Keep abreast of emerging technologies and industry trends in AI, ML, NLP, computer vision, and automation. - Provide technical leadership and mentorship to engineering teams. - Engage in pre-sales and client interactions to define solution strategies and roadmaps. Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - Proven experience in architecting and deploying Generative AI solutions in production environments on Azure, GCP, AWS, etc. - Strong knowledge of AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn. - Experience with automation platforms like UiPath, Automation Anywhere, Power Automate. - Proficiency in cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes). - Solid understanding of data engineering, APIs, and microservices architecture. - Excellent communication and stakeholder management skills. Preferred Skills: - Certifications in cloud architecture or AI/ML (e.g., AWS Certified Machine Learning, Azure AI Engineer). - Experience with MLOps, model monitoring, and CI/CD pipelines. - Familiarity with ethical AI practices and data privacy regulations.,