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iMerit Technology • Bengaluru, Karnataka, India
Role & seniority: AI Automation Engineering Manager, senior/lead level (10+ years)
Location & work type: On-site, Bengaluru area; full-time
Languages: Python, Java, C++
AI/ML: TensorFlow, PyTorch; data prep and model evaluation
Automation / platforms: process automation; low-code/no-code tools
Cloud & deployments: AWS, Azure, GCP; Docker, Kubernetes; MLOps pipelines
Data/QA: data preprocessing; QA methodologies; test case design
Design, develop, and implement AI-powered automated solutions; deploy to production and integrate with IT/OT systems
Train/refine ML models, prepare data, build deployment pipelines, monitor performance, and optimize for scale, security, and reliability
Collaborate with cross-functional stakeholders, document processes, provide training, and ensure quality assurance
10+ years in automation or ML automation; strong process automation capabilities
Proficiency in Python (and/or Java/C++), ML frameworks (TensorFlow, PyTorch)
Experience with cloud services (AWS/Azure/GCP), containers (Docker/Kubernetes), and MLOps
Familiarity with data preprocessing, model evaluation, testing, and QA practices
Strong problem-solving, analytical, and communication skills
Experience with low-code/no-code automation platforms
Certifications or prior work in AI/automation domains
Experience training large teams (Infrastructure/Secu
Job Role: AI Automation Engineering Manager
Role Description
This is a full-time, on-site role for an AI Automation professional located in the Bengaluru area. An AI Automation Manager designs, develops, and implements automated solutions that use artificial intelligence to improve business processes. This role involves developing AI models, creating automated workflows, and integrating AI with existing systems to reduce manual effort and increase efficiency and productivity.
Key responsibilities include coding automation solutions, collaborating with cross-functional teams, training models, and monitoring system performance. The AI automation expert will be responsible for building and implementing automation solutions, identifying inefficiencies, and optimizing work processes. Key responsibilities also include testing, troubleshooting issues, and ensuring adherence to quality assurance standards for automated systems.
Design and Develop Solutions: Create and program automated systems that use AI to solve specific business challenges.
AI Model Development: Train and refine machine learning models, prepare data, and select appropriate model architectures.
Implementation: Deploy AI-powered automation into production environments and integrate AI with other IT and operational technology (OT) systems.
Collaboration: Work with stakeholders and other engineering teams to understand requirements and define automation goals.
Testing and Maintenance: Simulate and test automation processes, troubleshoot malfunctions, and continuously monitor and upgrade existing systems.
Documentation and Training: Document all aspects of the automation process and provide technical support and training to end-users.
Performance Optimization: Analyze and improve the performance, scalability, and security of automated systems.
10 years of experience in automation or machine learning automation. Strong skills in Process Automation and Automation with the ability to optimize workflows and implement AI-driven solutions across infrastructure. Holding training sessions with the larger team to educate the Infrastructure and Information Security team on AI fundamentals and automation. Troubleshooting and problem-solving skills to address system inefficiencies and errors effectively. Experience in designing and executing test cases to ensure system reliability. Knowledge of quality assurance practices and methodologies for maintaining high standards. in automated systems. Strong analytical abilities and a detail-oriented mindset. Proven proficiency in programming languages such as Python, Java, or C++. Proven experience with AI/ML techniques and deep learning frameworks such as TensorFlow or PyTorch. Familiarity with automation tools and platforms, including low-code/no-code solutions. Experience with cloud services (e.g., AWS, Azure, and GCP) and containerization. technologies (e.g., Docker, Kubernetes) are often required. Knowledge of data science principles, including data preprocessing and model evaluation. Experience with MLOps principles and building deployment pipelines. Strong problem-solving and analytical skills. Good communication skills to collaborate with teams and explain technical concepts. Relevant certifications or prior experience in AI and automation technologies are a plus. Bachelor’s degree in Computer Science, Engineering, or a related field.