
Automation Systems Engineer
24 hours ago
Key Responsibilities
Design & Development
• Design, develop, and maintain robust automation frameworks and scripts primarily using Python and AI-powered applications.
• Build intelligent bots and automation workflows using RPA tools and integrate them with AI services.
• Design frameworks for end-to-end test automation of robotic and enterprise systems.
AI & Machine Learning Integration
• Leverage AI/ML, computer vision, and natural language processing (NLP) to enable smarter robotic automation.
• Train and deploy AI models for object detection, predictive analytics, and anomaly detection.
• Collaborate with data scientists to incorporate machine learning models into automation pipelines.
System Integration
• Integrate robotic and AI automation with enterprise systems, APIs, and cloud services.
• Ensure seamless operation with CI/CD pipelines and DevOps environments.
• Work on digital twins/simulation frameworks to validate robotic automation before deployment.
Monitoring & Optimization
• Implement monitoring, logging, and real-time performance tracking of automated systems.
• Continuously evaluate automation effectiveness and optimize for efficiency, scalability, and reliability.
• Contribute to knowledge sharing, documentation, and reusable automation libraries.
Collaboration
• Work closely with cross-functional teams (software engineers, QA, AI/ML experts, operations).
• Support senior engineers in developing enterprise-level automation strategy.
• Engage in proof-of-concept projects for emerging automation and AI technologies.
Required Skills & Qualifications
• Education: Bachelor's degree in Computer Science, Robotics, AI, Electrical Engineering, or related field.
• Experience: 3–5 years in automation engineering, with exposure to robotics and AI-driven automation.
Technical Expertise
• Hands-on experience with robotic automation frameworks (ROS, PLCs, IoT protocols, robotic arms).
• Strong programming skills in Python, Java, or C++.
• Familiarity with RPA tools (UiPath, Blue Prism, Automation Anywhere).
• AI/ML knowledge: computer vision, NLP, TensorFlow, PyTorch, or equivalent frameworks.
• Experience with cloud platforms (AWS, Azure, GCP) and DevOps pipelines.
Soft Skills
• Strong analytical and problem-solving skills.
• Ability to work in collaborative, cross-disciplinary teams.
• Curiosity and adaptability to learn and apply new automation/AI technologies.
• Be a quick learner
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