Solutions Engineer Cloud AI

Key Responsibilities: Cloud & Infrastructure Support - Assist in the implementation and maintenance of cloud-based solutions on platforms such as AWS, Azure, or GCP. - Support cloud-native application development, deployment, and monitoring. - Work with containers, APIs, and microservices-based environments. - Follow security, governance, and compliance requirements as defined by the organization. Software Development & Engineering - Develop, test, and maintain software applications using programming languages such as Python, Java, or similar technologies. - Participate in the software development lifecycle, including requirements understanding, design support, coding, testing, deployment, and documentation. - Build and integrate APIs, backend services, and application components. - Ensure code quality, maintainability, and adherence to development standards. AI & Data-Driven Solutions - Support the implementation of AI/ML-enabled features and automation use cases. - Work with data pipelines, model integration, and AI-based application components under guidance from senior team members. - Collaborate with data and engineering teams to integrate AI capabilities into business applications. DevOps & Automation - Support CI/CD pipeline activities and deployment automation. - Work with DevOps tools for build, deployment, version control, and monitoring. - Assist in troubleshooting deployment, application, and infrastructure issues. Stakeholder & Team Collaboration - Work with business and technical stakeholders to understand requirements and convert them into technical tasks. - Collaborate with developers, QA, DevOps, and infrastructure teams to deliver project outcomes. - Prepare technical documentation and provide regular progress updates. - Support client-facing or internal project discussions when required. Requirements: Experience - Minimum 3 years of experience in IT, software development, cloud engineering, or related roles. - Hands-on experience in application development and cloud-based implementations. - Exposure to AI/ML solutions, automation, or data-driven applications will be an advantage. Technical Skills - Experience with cloud platforms such as AWS, Azure, or GCP. - Programming experience in Python, Java, or similar languages. - Knowledge of APIs, microservices, and system integration. - Familiarity with Docker, Kubernetes, or containerized environments. - Understanding of DevOps practices, CI/CD pipelines, and automation tools. - Basic knowledge of AI/ML frameworks, data pipelines, or analytics platforms is advantageous. - Familiarity with databases, SQL, and application support activities. Soft Skills - Good communication and interpersonal skills. - Strong analytical and problem-solving abilities. - Ability to work independently and as part of a team. - Willingness to learn new technologies and adapt to project requirements. - Good documentation and stakeholder coordination skills. Qualifications - Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. - Relevant certifications in cloud, software development, DevOps, or AI/ML will be advantageous. Preferred Experience - Experience in cloud-based software projects. - Exposure to regulated industries such as BFSI, government, or healthcare is advantageous. - Experience working in consulting, implementation, or client-facing environments is preferred.