Sr Java/React Developer

Role Title: Sr Java/React Developer

Work Experience: 5+ years

Educational Qualification: Bachelor’s degree in computer science, Information Technology, or a related field

Work Location: Chennai

Work Mode: Hybrid

Key Responsibilities:
• 5+ years of hands-on experience in Java and React applications
• 5+ years of experience with natural language processing (NLP) techniques and toolsStrong background in AI, machine learning, deep learning, and data science.
• Proficiency in low-code/no-code platforms such as Mendix, Microsoft PowerApps, or Appian.
• Proficiency in AI frameworks and libraries (e.g., TensorFlow, PyTorch, Keras).
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for AI deployment.
• Understanding of software engineering principles, APIs, and system integrations.
• Excellent problem-solving skills and attention to detail.
• Ability to communicate technical concepts clearly and effectively.
• Proven experience in project management and leadership roles.
• Identify opportunities for automation, optimization, and AI-driven innovation in business processes using low-code approaches
• Design machine learning models, neural networks, and other AI algorithms.
• Integrate AI solutions with existing IT infrastructure.
• Oversee data collection, preprocessing, and storage for AI applications.
• Define data pipeline architectures for efficient AI model training and deployment
• Lead strategic meetings with Customer IT/Business and user groups to define GenAI-driven requirements
• Model testing and refinements, deploying models to production, and conducting Gen AI fit-gap analysis and ROI assessments
• Define cognitive architectures, conduct Gen AI research, and publish industry watch newsletters
• Documentation related to model design, testing, and implementation, as well as reports on model performance and improvements
• Stay up-to-date with the latest trends in AI, machine learning, and related technologies.
• Provide expertise in model selection, evaluation, and tuning for optimal performance.
• Ensure successful deployment of AI models into production environments.
• Set up monitoring systems to track AI performance and make improvements.
• Ensure that AI solutions comply with legal, ethical, and regulatory standards
• Managing computational resources, scaling infrastructure, ensuring AI infrastructure security, and aligning Gen AI security needs with the Enterprise Security Framework
• Establishing auditing and compliance mechanisms, budget allocation, and oversight