AI Engineer

Key Responsibilities

• Design, develop, and deploy AI/ML solutions to address business challenges.
• Build, train, fine-tune, and optimize Machine Learning and Generative AI models.
• Develop AI-powered applications using Python and leading AI/ML frameworks.
• Implement Large Language Model (LLM) solutions, prompt engineering, and Retrieval-Augmented Generation (RAG) pipelines.
• Build and maintain scalable AI services, APIs, and model deployment pipelines.
• Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions.
• Optimize model performance, scalability, and inference efficiency.
• Monitor AI models in production and ensure reliability, security, and compliance.
• Stay up to date with emerging AI technologies and recommend innovative solutions.

Required Skills

• Minimum 5+ years of relevant experience in AI/ML Engineering.
• Strong proficiency in Python (Mandatory).
• Hands-on experience with Machine Learning, Deep Learning, and Generative AI.
• Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
• Strong knowledge of Large Language Models (LLMs), Prompt Engineering, RAG, Embeddings, and Vector Databases.
• Experience with AI orchestration frameworks such as LangChain or LlamaIndex.
• Knowledge of REST APIs, Microservices, and model deployment.
• Experience with cloud platforms such as AWS, Azure, or GCP and their AI/ML services.
• Strong understanding of SQL, data preprocessing, feature engineering, and model evaluation.
• Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• Experience with OpenAI, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or SageMaker.
• Experience with vector databases such as Pinecone, Milvus, Weaviate, or ChromaDB.
• Exposure to NLP, Computer Vision, or Recommendation Systems.
• AI/ML or cloud certifications are an added advantage.