Generative AI Engineer

We are seeking a highly skilled Generative AI Engineer, Large Language Models (LLMs), and workflow automation. The ideal candidate will design, develop, and deploy scalable AI-driven solutions, integrating intelligent systems into real-world business processes. Key Responsibilities AI/ML & Model Development Develop and implement machine learning and deep learning models for various use cases Work with supervised and unsupervised learning techniques, including model evaluation and optimization Train, fine-tune, and deploy ML models in production environments LLMs & Generative AI Build applications using Large Language Models (LLMs), including OpenAI and open-source models (e.g., LLaMA, Mistral) Design and optimize prompt engineering strategies Develop Retrieval-Augmented Generation (RAG) systems using embeddings and vector search Fine-tune domain-specific AI models for business use cases Automation & Workflow Orchestration Design and implement AI-driven automation workflows using tools like n8n, Zapier, or similar platforms Integrate AI capabilities into business processes such as sales, compliance, and security operations Build scalable, reliable automation systems Backend & System Integration (Good to Have) Develop backend services using Python (preferred) and/or Node.js Build and integrate APIs (REST, GraphQL) Work with microservices-based architectures Data Engineering & Pipelines Design and manage ETL pipelines for structured and unstructured data Build real-time data processing systems Work with vector databases such as Pinecone, Weaviate, or FAISS MLOps & Deployment Deploy, monitor, and maintain ML models in production Implement model lifecycle management and performance tracking Utilize tools such as MLflow, Weights & Biases, etc.

Work with Docker, Kubernetes, and CI/CD pipelines Cloud & Infrastructure Deploy and manage AI systems on cloud platforms (AWS, Azure, or GCP) Ensure scalability, reliability, and performance of production systems Required Skills & Qualifications Strong foundation in Machine Learning, Deep Learning, and NLP experience- 3-4 years Hands-on experience with LLMs, prompt engineering, and RAG architectures Experience with automation tools (n8n, Zapier, etc.) Proficiency in Python; Node.js is a plus Experience with APIs, data pipelines, and system integration Familiarity with vector databases and embeddings Knowledge of MLOps practices and deployment tools Experience working with cloud platforms (AWS/Azure/GCP) Preferred Qualifications Experience building end-to-end AI products Exposure to real-time AI applications and scalable architectures Strong problem-solving and system design skills