Job
Description
As a Full Stack AI Automation Engineer, your role involves designing, building, and maintaining intelligent automation systems that utilize AI to streamline business processes. You will be responsible for developing end-to-end solutions, connecting APIs, automating workflows, and deploying scalable AI-powered applications. This position requires a cross-functional skill set, combining expertise in AI/ML, backend development, frontend interfaces, and DevOps. Key Responsibilities: - Design and develop full-stack automation platforms using Python for backend logic and modern frontend frameworks - Build and integrate AI-powered workflows using LLMs, machine learning models, and intelligent decision-making systems - Create and maintain RESTful APIs and GraphQL endpoints for automation services and third-party integrations - Deploy and manage applications on Google Cloud Platform (GCP) using serverless functions, containers, and managed services - Implement CI/CD pipelines, maintain code repositories using GitHub, and follow proper branching strategies and code reviews - Collaborate using Jira for project management and Confluence for technical documentation and knowledge sharing - Monitor system performance, implement error handling, and ensure high availability of automation services - Work closely with stakeholders to identify automation opportunities and translate business requirements into technical solutions - Optimize existing automations for performance, cost-efficiency, and scalability - Maintain comprehensive documentation and establish best practices for the automation platform Qualifications Required: - Hands-on engineering mindset with the ability to architect and execute complex automation solutions - Self-starter attitude with strong problem-solving skills and ability to work independently - 5+ years of Python development experience with expertise in frameworks like FastAPI, Django, or Flask - 3+ years of full-stack development experience with modern frontend frameworks (React, Vue.js, or Angular) - 2+ years of AI/ML integration experience working with LLMs, APIs (OpenAI, Anthropic), and ML frameworks - Proven experience with API development including RESTful services, authentication, rate limiting, and documentation - Strong GCP expertise including Cloud Functions, Cloud Run, BigQuery, Vertex AI, and infrastructure management - Advanced Git/GitHub skills including Actions, project management, and collaborative development workflows - Proficiency with Jira for agile project management and Confluence for technical documentation - Experience with automation frameworks and workflow orchestration tools - Knowledge of database design (both SQL and NoSQL) and data processing at scale - Understanding of DevOps practices including containerization (Docker), CI/CD, and monitoring - Strong system design skills with the ability to architect scalable, maintainable solutions Please note that this is a contractual/temporary job with a duration of 6 months. The work location is fully remote, offering flexibility in working hours and various benefits such as paid time off, global team culture, learning opportunities, and supportive environment. As a Full Stack AI Automation Engineer, your role involves designing, building, and maintaining intelligent automation systems that utilize AI to streamline business processes. You will be responsible for developing end-to-end solutions, connecting APIs, automating workflows, and deploying scalable AI-powered applications. This position requires a cross-functional skill set, combining expertise in AI/ML, backend development, frontend interfaces, and DevOps. Key Responsibilities: - Design and develop full-stack automation platforms using Python for backend logic and modern frontend frameworks - Build and integrate AI-powered workflows using LLMs, machine learning models, and intelligent decision-making systems - Create and maintain RESTful APIs and GraphQL endpoints for automation services and third-party integrations - Deploy and manage applications on Google Cloud Platform (GCP) using serverless functions, containers, and managed services - Implement CI/CD pipelines, maintain code repositories using GitHub, and follow proper branching strategies and code reviews - Collaborate using Jira for project management and Confluence for technical documentation and knowledge sharing - Monitor system performance, implement error handling, and ensure high availability of automation services - Work closely with stakeholders to identify automation opportunities and translate business requirements into technical solutions - Optimize existing automations for performance, cost-efficiency, and scalability - Maintain comprehensive documentation and establish best practices for the automation platform Qualifications Required: - Hands-on engineering mindset with the ability to architect and execute complex automation solutions - Self-starter attitude with strong problem-solving skills and
