Solution Architect

Role: Solution Architect (AI, MCP & Cloud Platforms)

Remote | Full-Time

Required Experience: 12+ Years

Location: Pune, India

About the Role:

CODVO.AI is seeking a highly experienced Solution Architect to lead the design, architecture, and delivery of AI-driven, MCP-enabled solutions and cloud-native enterprise platforms. This role requires deep expertise in software architecture, AI application development, cloud engineering, and modern software development practices. You will define technical strategy, establish engineering standards, and guide teams in building scalable, secure, and maintainable solutions across Azure and multi-cloud environments.

Key Responsibilities

• Own end-to-end solution architecture, technical design, and implementation strategy for AI-driven applications and enterprise platforms.
• Design and develop AI-enabled workflows, agentic applications, and integrations using the Model Context Protocol (MCP).
• Define architecture patterns for tool integration, context management, API orchestration, and AI-to-enterprise system interactions.
• Lead cloud architecture and implementation initiatives on Microsoft Azure, with support for GCP environments.
• Establish best practices for security, scalability, reliability, observability, and maintainability.
• Evaluate technology choices, architectural trade-offs, and build-versus-buy decisions.
• Conduct architecture reviews, mentor engineering teams, and provide hands-on technical leadership.
• Drive adoption of AI-assisted software development and modern engineering practices across the SDLC.
• Collaborate with product, engineering, DevOps, security, and QA teams to ensure successful solution delivery.
• Support compliance and regulated-environment requirements, including FedRAMP-related considerations where applicable.

Required Skills:

• 12+ years of experience in solution architecture, software engineering, and distributed systems.
• Strong expertise in designing and implementing cloud-native applications and enterprise integrations.
• Hands-on experience with Microsoft Azure, including security, identity, networking, monitoring, and deployment services.
• Experience with multi-cloud architectures and familiarity with Google Cloud Platform (GCP).
• Practical experience building LLM-powered applications, AI agents, tool-calling frameworks, and MCP-based integrations.
• Strong understanding of APIs, microservices, event-driven architectures, data flows, and system integration patterns.
• Experience with CI/CD pipelines, infrastructure automation, observability, and secure software development practices.
• Ability to lead technical teams while remaining hands-on with architecture and implementation challenges.
• Excellent problem-solving, stakeholder management, and communication skills.