Python Developer – GenAI

7 days ago

bangalore, India PROADSW3 Relations pvt. ltd. Full time

📌 Hiring: Python Developer – GenAI & Agentic AI | 5–7 Years | Bangalore/Remote | Immediate Joiners📍 Location: Bangalore / Remote 🧾 Experience: 5–7 Years 💰 Budget: 1.6 – 1.7 LPM 🕒 Notice Period: Immediate (Bench resources only) 📝 Mode: Remote/Hybrid ⚠️ Note: Candidates must have ESI/Medical Insurance, EPFO Registration, PT Registration, Labour Welfare Fund Registration, Shop Act Registration, and GST Registration. Only profiles with these compliance documents will be considered.✨ About the RoleWe are looking for an experienced Python Developer specialized in Generative AI (GenAI) and Agentic AI. The ideal candidate will be proficient in LLM-based application development, RAG pipelines, AI agents, LangChain/LangGraph, and cloud AI services. You will design and deploy scalable AI-driven solutions used across enterprise environments.🔧 Key ResponsibilitiesDevelop GenAI Applications: Build and optimize AI solutions using Python, LangChain, LangGraph, MCP, and AgentOps.LLM Integration: Work with Azure AI, AWS Bedrock, OpenAI, Anthropic, and other LLM providers for text, multimodal, and agent workflows.RAG Architecture: Implement Retrieval-Augmented Generation pipelines with vector DBs (Pinecone, Chroma, Weaviate, FAISS).Fine-tuning & MLOps: Fine-tune LLMs for domain tasks; build CI/CD pipelines for ML models using MLOps tools and best practices.Agentic AI Systems: Design multi-agent workflows with orchestration, memory, planning, and error-handling capabilities.Cloud Deployment: Deploy models/applications on AWS (Lambda, EC2, S3, Bedrock, SageMaker) and Azure AI.Performance & Cost Optimization: Optimize model response time, scalability, and cloud compute cost.Cross-functional Collaboration: Work closely with Data Science, DevOps, and Product teams to deliver robust AI solutions.🎯 Required Skills & QualificationsStrong proficiency in Python and backend development.Hands-on experience with LangChain, LangGraph, MCP, AgentOps.Strong understanding of RAG pipelines and vector DBs (Pinecone, Chroma, Weaviate, FAISS).Experience in LLM fine-tuning and prompt engineering.Solid knowledge of MLOps (CI/CD, monitoring, model deployment).Experience using cloud AI platforms: AWS Bedrock, Azure AI, SageMaker, GCP Vertex AI (preferred).Understanding of Agentic AI (multi-agent orchestration, planning, memory).Familiarity with Docker, Kubernetes, Terraform, GitOps.Strong analytical, debugging, and problem-solving skills.⭐ Preferred QualificationsExperience with multimodal models (text, image, audio).Exposure to enterprise AI compliance and security frameworks.Knowledge of ISO/IEC AI governance standards.Contributions to open-source AI/ML projects.📨 How to ApplyIf your profile matches and you meet the compliance requirements, please share your resume at [Add Email / Apply Link]. Immediate joiners are highly preferred.

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