Solution Architect

You are an experienced Solution Architect with a solid background in software architecture and a good understanding of AI-based products and platforms. Your main responsibility will be to design robust, scalable, and secure architectures that support AI-driven applications and enterprise systems. In this role, you will collaborate closely with cross-functional teams, including data scientists, product managers, and engineering leads, to ensure the alignment of business needs, technical feasibility, and AI capabilities. Your key responsibilities will include architecting end-to-end solutions for enterprise and product-driven platforms, such as data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. You will guide teams in selecting appropriate technologies, tools, and design patterns for building scalable systems. Additionally, you will work with AI/ML teams to understand model requirements and facilitate their smooth deployment and integration into production environments. In this role, you will define system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. Furthermore, you will collaborate with stakeholders to translate business requirements into technical solutions, emphasizing scalability, performance, and security. Your leadership will be crucial in promoting best practices for software development, DevOps, and cloud-native architecture. You will also conduct architecture reviews to ensure compliance with security, performance, and regulatory standards. To be successful in this role, you should have at least 10 years of experience in software architecture or solution design roles. You should demonstrate expertise in designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. Hands-on experience with major cloud providers like AWS, GCP, or Azure is essential. Familiarity with AI/ML platforms and components, data architectures, containerization, DevOps principles, and the ability to lead technical discussions are also required skills. Preferred qualifications include exposure to AI model lifecycle management, infrastructure-as-code tools like Terraform or Pulumi, knowledge of GraphQL, gRPC, or serverless architectures, and previous experience in AI-driven product companies or digital transformation programs. In return, you will have the opportunity to play a high-impact role in designing intelligent systems that drive the future of AI adoption. You will work alongside forward-thinking engineers, researchers, and innovators, with a strong focus on career growth, learning, and technical leadership. The compensation offered is competitive and reflective of the value you bring to the role.,