AI Automation Engineer

We are looking for an AI Automation Engineer to design and deploy cutting-edge Generative AI systems combining Python, LLMs, and cloud-based AI automation. The ideal candidate should have hands-on experience with AI agentic workflows, Retrieval-Augmented Generation (RAG) architectures, and enterprise-scale automation.

Key Responsibilities:
• Design, Fine-tune, and deploy AI models using Python and AI libraries, integrating LLMs for intelligent automation.
• Preprocess data, perform feature engineering, and improve model performance.
• Implement RAG systems with vector databases (Pinecone, Milvus) for knowledge-intensive automation.
• Design and Deploy agentic and hyper-automation solutions integrating LLMs..
• Optimize AI model inference, scalability, and real-time decision-making.
• Ensure security, scalability, and reliability of deployed AI models and automation workflows.
• Hands-on experience with REST APIs and cloud platforms (AWS, Azure, GCP) for AI model deployment.
• Design self-improving automation using reinforcement learning and adaptive ML techniques

Requirements:
• 4+ years' experience in Python and Generative AI technologies (Hugging Face, LlamaIndex, LangChain).
• 2+ years' experience in LLM fine-tuning, optimization, quantization, and prompt engineering.
• Proficiency with vector databases (Pinecone, FAISS, Milvus) and GPU-accelerated training/inference.
• Experience in cloud-based AI deployment (AWS SageMaker, Azure ML, Vertex AI).
• Strong knowledge of AI agent architectures and workflow automation.

Good to Have Skills
• Experience with front-end frameworks (Angular, React) and back-end development (Node.js).
• Familiarity with microservices architecture and API-driven AI integration.
• Exposure to AI-driven analytics, intelligent chatbots, and AI-powered business process automation.
• Experience with Embedding Search, Document Scraping, and Chunking for efficient data retrieval and processing
• Exposure to AI agentic workflows.

Key AI Focus Areas
1. Large Language Models (LLMs)
2. Retrieval-Augmented Generation (RAG) Systems
3. AI Agents & Decision Intelligence
4. Multimodal AI & Automation
5. Self-Optimizing Workflows

Education & Certifications:
• Bachelor's or master's degree in computer science, Engineering, or a related field
• Certification in Python, Cloud and AI platforms (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate, Google Cloud AI certifications) is a strong plus