Gen AI Engineer
- Posted 13 days ago
- Be among the first 10 applicants
Job Description
Role: AI Engineer / AIML Data Science and Gen AI
Experience : 6 to 9 Years
Location : Bangalore
Notice Period : Immediate to 90 days
Mode of Interview : Virtual / In-Person
Mandatory skills: AI Engineer Python, Langchain, LangGraph, Agentic AI, API, LLMs
Role & Responsibilities
Experience : 6 to 9 Years
Location : Bangalore
Notice Period : Immediate to 90 days
Mode of Interview : Virtual / In-Person
Mandatory skills: AI Engineer Python, Langchain, LangGraph, Agentic AI, API, LLMs
Role & Responsibilities
- Design, develop, and deploy Agentic AI systems using Python
- Build autonomous AI agents capable of planning, reasoning, and tool usage
- Develop and manage multi-agent workflows and orchestration pipelines
- Integrate LLMs with APIs, databases, and enterprise applications
- Implement Retrieval-Augmented Generation (RAG) pipelines
- Develop scalable backend services and microservices for AI applications
- Optimize performance, latency, and cost of AI systems in production
- Collaborate with Data Science, Engineering, and Product teams
- Ensure best practices in testing, monitoring, and deployment of AI systems
More Info
About Company
Skills:
Api, Python, LangGraph, Langchain, Agentic AI, LLMs
Skills:
Automated Testing, Microservices, Angular, React, Flask, Microsoft Azure, Python, Cybersecurity, Django, Databricks, Data Privacy, FastAPI, Restful Apis, vector databases, Claude, ChatGPT, AI model evaluation, Next.js, OpenAI APIs, observability, fine-tuning, Anthropic APIs, Regulatory Compliance, AI governance
Skills:
Kubernetes, MLops, AWS, FastAPI, Python, Azure, Docker, Azure ML, Llm, OpenSearch, ChromaDB, Semantic Kernel, GenAI, Hugging Face, RAG, LangChain, AI Agents, Pinecone, FAISS, LangGraph
Skills:
Gcp, Docker, Rest Apis, Azure, Python, AWS, LLMs, LangChain, RAG architecture, vector databases, Agentic AI, microservices architecture, LlamaIndex
Skills:
Aws, Python, Typescript, Ai