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