Job
Description
As a Solution Architect at Techvantage.ai, you will play a key role in designing robust, scalable, and secure architectures to support AI-driven applications and enterprise systems. Working closely with cross-functional teams, you will bridge the gap between business needs, technical feasibility, and AI capability. Your responsibilities will include: - Architecting end-to-end solutions for enterprise and product-driven platforms, encompassing data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. - Guiding teams in selecting appropriate technologies, tools, and design patterns for building scalable systems. - Collaborating with AI/ML teams to understand model requirements and ensure seamless deployment and integration into production. - Defining system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. - Translating business needs into technical solutions with a focus on scalability, performance, and security. - Providing leadership on best practices for software development, DevOps, and cloud-native architecture. - Conducting architecture reviews to ensure alignment with security, compliance, and performance standards. Qualifications we seek in an ideal candidate include: - 10+ years of experience in software architecture or solution design roles. - Proven expertise in designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. - Hands-on experience with at least one major cloud provider: AWS, GCP, or Azure. - Familiarity with AI/ML platforms and components, such as integrating AI models, MLOps pipelines, or inference services. - Understanding of data architectures, including data lakes, streaming, and ETL pipelines. - Strong experience with containerization (Docker, Kubernetes) and DevOps principles. - Ability to lead technical discussions, make design trade-offs, and communicate effectively with technical and non-technical stakeholders. Preferred qualifications include exposure to AI model lifecycle management, prompt engineering, or real-time inference workflows, experience with infrastructure-as-code tools like Terraform or Pulumi, knowledge of GraphQL, gRPC, or serverless architectures, and previous work in AI-driven product companies or digital transformation programs. At Techvantage.ai, you will have the opportunity to design intelligent systems that drive AI adoption, collaborate with forward-thinking professionals, and focus on career growth and technical leadership. Compensation is competitive and commensurate with your skills and experience. As a Solution Architect at Techvantage.ai, you will play a key role in designing robust, scalable, and secure architectures to support AI-driven applications and enterprise systems. Working closely with cross-functional teams, you will bridge the gap between business needs, technical feasibility, and AI capability. Your responsibilities will include: - Architecting end-to-end solutions for enterprise and product-driven platforms, encompassing data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. - Guiding teams in selecting appropriate technologies, tools, and design patterns for building scalable systems. - Collaborating with AI/ML teams to understand model requirements and ensure seamless deployment and integration into production. - Defining system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. - Translating business needs into technical solutions with a focus on scalability, performance, and security. - Providing leadership on best practices for software development, DevOps, and cloud-native architecture. - Conducting architecture reviews to ensure alignment with security, compliance, and performance standards. Qualifications we seek in an ideal candidate include: - 10+ years of experience in software architecture or solution design roles. - Proven expertise in designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. - Hands-on experience with at least one major cloud provider: AWS, GCP, or Azure. - Familiarity with AI/ML platforms and components, such as integrating AI models, MLOps pipelines, or inference services. - Understanding of data architectures, including data lakes, streaming, and ETL pipelines. - Strong experience with containerization (Docker, Kubernetes) and DevOps principles. - Ability to lead technical discussions, make design trade-offs, and communicate effectively with technical and non-technical stakeholders. Preferred qualifications include exposure to AI model lifecycle management, prompt engineering, or real-time inference workflows, experience with infrastructure-as-code tools like Terraform or Pulumi, knowledge of GraphQL, gRPC, or serverless architectures, and previous work in AI-driven product companies or digital transformation progra
