AI Digital Engineer

Role & responsibilities

• Design and develop GenAI and AI-powered applications.
• Build and optimize RAG pipelines and AI Agent solutions.
• Develop scalable APIs and cloud-native microservices.
• Deploy, monitor, and maintain AI/ML models in production.
• Implement MLOps/LLMOps best practices.
• Collaborate with architects, data scientists, and business teams.
• Ensure AI security, governance, and Responsible AI compliance.
• Drive innovation using emerging AI technologies.

Key skills-

• Generative AI (GenAI)
• Large Language Models (GPT, Gemini, Claude, Llama)
• RAG (Retrieval Augmented Generation)
• Agentic AI & AI Agents
• Prompt Engineering
• LangChain, LlamaIndex, Semantic Kernel
• Python, SQL
• TensorFlow, PyTorch, Scikit-Learn
• Azure AI Foundry, Azure OpenAI, Vertex AI
• Docker, Kubernetes
• CI/CD, MLOps, LLMOps
• REST APIs & Microservices
• Vector Databases (Pinecone, FAISS, ChromaDB)
• MLflow, LangSmith, Prometheus