Job
Description
Job Title: Solution Architect – AI & Automation About the Role: We are seeking a highly skilled and visionary Solution Architect to lead the design and implementation of cutting-edge solutions in Artificial Intelligence (AI), Generative AI and Automation. This role requires a blend of technical expertise, strategic thinking, and leadership to drive innovation and deliver scalable, high-impact solutions across the organization. Experience Level: 10+ Years Experience in AI/ML, GenAI and automation domains Responsibilities: Design end-to-end AI and automation solutions aligned with business goals and technical requirements. Participate in business requirements discussions and arrive at solution, Technical architecture considering 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. Stay current with emerging technologies and industry trends in AI, ML, NLP, computer vision, and automation. Provide technical leadership and mentorship to engineering teams. Participate in pre-sales and client engagements to define solution strategies and roadmaps. Qualifications: Bachelor’s or master’s degree in computer science, Engineering, or related field. Proven experience in architecting and deploying Generative AI solutions in production environments in Azure, GCP, AWS etc. Strong knowledge of AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with automation platforms (e.g., 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.
