Artificial Intelligence Engineer

About Techwave TechnologiesTechwave Technologies is a technology consulting and solutions company focused on helping organizations leverage modern technologies to solve complex business challenges. We work across Artificial Intelligence, Machine Learning, Data Engineering, Cloud Computing, Software Development, and Digital Transformation.We are looking for an Artificial Intelligence Engineer to join our growing technology team and design, develop, deploy, and optimize production-ready AI and Machine Learning solutions.Position OverviewThe Artificial Intelligence Engineer will be responsible for building scalable AI/ML applications that solve real-world business problems. The ideal candidate will have strong programming skills, hands-on experience with Machine Learning and Generative AI, and the ability to take AI solutions from experimentation and prototyping through production deployment.You will work closely with software engineers, data engineers, data scientists, product teams, and business stakeholders to develop intelligent applications, predictive models, LLM-based solutions, and AI-powered automation.Key ResponsibilitiesDesign, develop, train, test, and deploy Artificial Intelligence and Machine Learning models for real-world business applications.Develop production-grade AI applications using Python, SQL, and modern AI/ML frameworks.Build and integrate Generative AI and Large Language Model (LLM) applications.Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, and enterprise knowledge sources.Implement prompt engineering, model evaluation, fine-tuning, and inference optimization techniques.Develop AI-powered agents and intelligent automation workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.Perform data preprocessing, feature engineering, exploratory data analysis, model development, and model validation.Work with structured, semi-structured, and unstructured data including text, documents, JSON, APIs, and databases.Develop and integrate REST APIs and microservices for AI/ML applications.Deploy AI/ML solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.Work with services such as AWS SageMaker, AWS Bedrock, Azure Machine Learning, Azure AI, or Google Vertex AI.Containerize applications using Docker and support deployment using Kubernetes or cloud-native services.Build and maintain MLOps/LLMOps pipelines for model deployment, monitoring, versioning, evaluation, and lifecycle management.Implement CI/CD workflows using tools such as GitHub Actions, Jenkins, or GitLab CI/CD.Monitor model performance, accuracy, latency, reliability, scalability, and resource utilization in production.Identify and troubleshoot model, data, API, and deployment issues.Implement appropriate AI security, data privacy, governance, and responsible AI practices.Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.Evaluate emerging AI technologies and recommend solutions that can improve business processes and customer experiences.Create technical documentation covering AI architectures, models, APIs, data pipelines, deployment processes, and model evaluation.