Senior software developer
1 week ago
Responsibilities Design, develop, and implement scalable and secure data integration pipelines and application connectors for Agent Space projects. Leverage i Paa S platforms, including Apigee and similar tools, to build robust APIs and integration layers that seamlessly connect Agent Space with diverse enterprise systems. Collaborate with Machine Learning Engineers and Data Scientists to ensure seamless data flow and integration for AI-powered solutions. Work closely with client teams to understand existing toolsets and data sources, ensuring effective deployment and integration of Agent Space functionalities. Develop and maintain high-quality codebases for data extraction, transformation, and loading (ETL) processes, ensuring data quality and integrity. Contribute to solution architecture discussions, focusing on integration patterns, API design, and data governance for complex, multi-industry problems. Implement best practices for software development, testing, and documentation, ensuring high-quality, production-ready solutions. Stay abreast of the latest advancements in Generative AI, LLMs, and cloud-native integration technologies, applying new knowledge to enhance solutions. Qualifications Education: Bachelor’s or Master’s Degree in Computer Science, Software Engineering, or a related technical field. Experience: Minimum 4-8+ years of professional experience as a Software Developer, with a strong emphasis on data integration, API development, i Paa S platforms. Skills: Strong analytical and problem-solving skills, with a proven ability to tackle complex, multi-industry challenges. Strong proficiency in any one of the programming languages such as Python, or Java, or Node.js. Thorough understanding and hands-on experience with API development, orchestration, and application integration using platforms like Apigee and Vertex AI. Solid understanding of API design principles (REST, g RPC) and experience with API management. Demonstrated experience with data and analytics concepts, including ETL/ELT processes and data warehousing. Good understanding of Generative AI and Large Language Models (LLMs). Proven experience working with cloud platforms, particularly Google Cloud Platform (GCP) services relevant to data and application integration (e.g., Cloud Functions, Pub/Sub, Big Query, Cloud Storage). Excellent communication and collaboration skills. Nice-to-Have Skills: Direct hands-on experience with Google's Agent Space platform Experience with i Paa S tools such as Mule Soft, Dell Boomi, or similar. Knowledge of data governance and security best practices in cloud environments. Familiarity with real-time data streaming technologies. Experience with version control systems (Git) and CI/CD pipelines. Experience with Agent Space connectors to client tools such as Share Point, Jira, Confluence, Salesforce, Slack, Service Now, and One Drive.
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