AI Engineer

Position: AI Engineer

Experience: 5-10 Years

Location: Bangalore

Notice Period: Immediate Joiner / Up to 30 Days

Job Summary :

We are seeking a highly skilled AI Engineer with hands-on experience in Python, Agentic AI, Generative AI, RAG (Retrieval-Augmented Generation), Machine Learning, and Large Language Models (LLMs) on any major cloud platform. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI solutions leveraging modern GenAI technologies.

Key Responsibilities :

• Design and develop AI/ML solutions using Python and modern AI frameworks.
• Build and implement Agentic AI systems leveraging LLMs and autonomous workflows.
• Develop and optimize RAG-based applications integrating vector databases and enterprise knowledge sources.
• Deploy and manage AI solutions on cloud platforms such as Azure, AWS, or GCP.
• Fine-tune, evaluate, and optimize Large Language Models for business use cases.
• Integrate GenAI solutions with enterprise applications and APIs.
• Work closely with cross-functional teams to translate business requirements into AI-driven solutions.
• Ensure scalability, security, and performance of AI applications.
• Stay updated with emerging trends in GenAI, Agentic AI, and Machine Learning technologies.

Required Skills :

• Strong programming experience in Python.
• Hands-on experience with Generative AI, Agentic AI, and RAG architectures.
• Solid understanding of Machine Learning concepts and model development.
• Experience working with LLMs such as OpenAI, Claude, Gemini, Llama, Mistral, etc.
• Knowledge of vector databases like Pinecone, ChromaDB, FAISS, or Weaviate.
• Experience with AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Hands-on experience with Azure OpenAI, AWS Bedrock, Vertex AI, or any cloud-based AI platform.
• Experience in API development and integration.
• Good understanding of prompt engineering and AI model evaluation techniques.

Preferred Skills :

• Experience with MLOps and AI model deployment pipelines.
• Knowledge of Kubernetes, Docker, and CI/CD for AI workloads.
• Familiarity with NLP, embeddings, and semantic search technologies.