Artificial Intelligence Engineer

We are seeking a skilled AI Engineer to design, develop, and deploy scalable AI solutions that leverage Machine Learning, Generative AI, and Large Language Models to solve complex business challenges. You will collaborate with cross-functional teams to build intelligent applications, optimize AI models, and drive innovation across enterprise products and platforms.

• Design, develop, and deploy production-ready AI and Generative AI solutions for enterprise use cases.
• Build and optimize machine learning and deep learning models using modern AI frameworks and tools.
• Develop intelligent applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.
• Integrate AI models with enterprise platforms, APIs, data pipelines, and business applications.
• Implement model evaluation, monitoring, and optimization techniques to improve accuracy, scalability, and performance.
• Collaborate with product managers, data scientists, and engineering teams to translate business requirements into AI-driven solutions.
• Develop and maintain scalable backend services and APIs supporting AI workloads.
• Contribute to code reviews, technical documentation, and engineering best practices.
• Strong programming skills in Python with hands-on experience in AI/ML development.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, or similar.
• Working knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and model fine-tuning techniques.
• Experience with vector databases, embeddings, retrieval systems, and RAG architectures.
• Understanding of responsible AI principles, model governance, security, and evaluation methodologies.

Good to Have

• Exposure to MLOps/LLMOps practices including model deployment, monitoring, experiment tracking, and version control.
• Experience with Docker, Kubernetes, CI/CD pipelines, and cloud-native application development.
• Knowledge of cloud AI services on Azure, AWS, or GCP.
• Experience working with distributed computing, data engineering pipelines, and big data technologies.
• Familiarity with AI agent frameworks, autonomous workflows, and multi-agent systems.