Company Description OPSERA is a modern technology consultancy that helps enterprises build secure, scalable, cloud-native platforms across AWS, Azure, GCP, OCI, Alibaba Cloud, and OpenStack. The company specializes in Platform Engineering, Cloud Transformation, DevSecOps, AI-driven automation, and application modernization to improve delivery speed and reliability. OPSERA focuses on creating resilient, secure platforms with reduced complexity and enhanced developer productivity. With deep experience in sectors such as banking, government, telecom, aviation, manufacturing, and large enterprises, the team combines strategic vision with hands-on engineering. OPSERA emphasizes outcome-driven delivery, deep technical expertise, and knowledge transfer to help clients lead in the digital era.Role Description This is a full-time remote role for an Artificial Intelligence Engineer at OPSERA. The AI Engineer will design, develop, and deploy AI and machine learning models that support platform engineering, DevSecOps, and intelligent automation solutions. Day-to-day responsibilities include building and optimizing models for pattern recognition, natural language processing, and predictive analytics, as well as integrating these models into production-grade software systems and pipelines. The role involves collaborating with cloud, DevOps, and platform engineering teams to implement AI-driven capabilities, improve observability, and enable automated remediation and intelligent delivery pipelines. The AI Engineer will also contribute to solution design, conduct experiments, evaluate model performance, and document and present technical findings to both technical and non-technical stakeholders.Qualifications Strong foundation in Computer Science and Software Development, including data structures, algorithms, APIs, and production-grade coding practices.Hands-on experience with Neural Networks and Pattern Recognition, including designing, training, tuning, and deploying deep learning models.Practical knowledge of Natural Language Processing (NLP), such as text classification, information extraction, embeddings, and LLM-based solutions.Proficiency with modern ML/AI tools and frameworks (e.g., Python, PyTorch or TensorFlow, scikit-learn, transformers libraries) and experience with ML lifecycle tools (e.g., MLflow, Kubeflow, or similar).Experience deploying AI workloads on cloud platforms (AWS, Azure, or GCP), including containerization (Docker), orchestration (Kubernetes), and CI/CD integration.Familiarity with MLOps practices, observability, model monitoring, and continuous improvement in production environments.Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.Strong analytical and problem-solving skills