Responsibilities:

The responsibilities of the Solution Architect shall include, but not be limited to, the following:

• Design and oversee the end-to-end architecture of an IoT platform with AI capabilities, ensuring seamless integration of IoT devices, machine learning models, cloud infrastructure (GCP), and web applications.
• Define and implement architectural strategies for leveraging AI/ML technologies, including Vertex AI for model training and deployment, and Llama models for advanced AI functionalities such as predictive analytics or natural language processing.
• Collaborate with stakeholders (e.g., Product Manager, Data Scientists, Machine Learning Engineers) to gather requirements and translate them into scalable, secure, and high-performance system designs.
• Architect data pipelines and integration workflows to support real-time data streaming from IoT devices, using protocols like MQTT or CoAP, and ensure efficient data flow to AI models and storage systems.
• Design microservices-based architectures to enable modular development, deployment, and scalability, integrating with APIs for inter-service communication and external systems.
• Select and recommend appropriate technologies, frameworks, and tools (e.g., GCP services like BigQuery, Pub/Sub, Cloud Functions) to meet project goals while optimizing cost, performance, and reliability.
• Ensure system scalability, fault tolerance, and high availability by implementing best practices for cloud architecture, load balancing, and disaster recovery.
• Define and enforce security standards across the platform, including data encryption, secure API communication (e.g., OAuth, JWT), and compliance with industry regulations for IoT and AI applications.
• Work closely with the DevOps Engineer to design infrastructure as code (IaC) using tools like Terraform, and support CI/CD pipelines for automated deployment of architectural components.
• Collaborate with the Integration Engineer to ensure seamless API-driven integrations between IoT devices, AI models, and the web application, enabling features like real-time analytics and automation.
• Provide technical leadership and guidance to development teams (e.g., Fullstack Developers, Software Developers) on architectural best practices, design patterns, and implementation strategies.
• Create and maintain comprehensive architectural documentation, including system diagrams, data flow models, and technical specifications, to support team collaboration and future maintenance.
• Monitor and evaluate system performance, identifying bottlenecks and recommending optimizations to ensure the platform meets SLAs for latency, throughput, and uptime.
• Stay updated on emerging technologies and industry trends in IoT, AI/ML, and cloud computing, and propose innovative solutions to enhance the platform’s capabilities.

Skills

Qualifications:

The qualifications for the Solution Architect shall include, but not be limited to, the following:

• Bachelor’s or Master’s degree in Computer Science, IT, or related field.
• 5+ years in solution architecture, with 2+ years on AI/ML and/or IoT projects.
• Expertise in Vertex AI and Llama models for AI/ML solutions.
• Strong experience with GCP (e.g., BigQuery, Pub/Sub, Cloud Functions).
• Proficiency in designing microservices and APIs (REST, GraphQL).
• Knowledge of IoT protocols (MQTT, CoAP) and real-time data streaming (e.g., Kafka).
• Familiarity with Docker, Kubernetes, and Terraform for cloud deployments.
• Understanding of security practices (e.g., OAuth, JWT, encryption).
• Excellent problem-solving and communication skills.
• Experience in Agile/Scrum environments.
• (Preferred) Google Cloud Professional Cloud Architect certification.