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Director - Talent Acquisition Β· Treyansh
14d ago

Agentic AI EngineerTreyansh

Want to build the next generation of AI-powered applications? This is your opportunity to work on cutting-edge Generative AI, Production RAG, and Agentic AI solutions with one of the industry's leading AI teams. Apply @Aarti.vohra@treyansh.co.in , Subject Agentic AI Engineer πŸ“… Face-to-Face Interview Drive Interview Date: 24th October 2026 βœ… 2 Interview Rounds βœ… Final Results on the Same Day βœ… Immediate Offer Rollout for Selected Candidates Only Immediate Joiners who can attend the complete interview process without any other interview commitments on the same day should apply. πŸ’Ό Position Agentic AI Engineer πŸ“ Location Bangalore 🏒 Work Mode Hybrid – Minimum 12 Work From Office Days per Month πŸ‘¨β€πŸ’» Experience 3–7 Years (Minimum 3 Years of Relevant AI/ML Engineering Experience) πŸš€ About the Role We are looking for passionate Agentic AI Engineers to design, develop, and deploy enterprise-scale AI solutions powered by LLMs, Production RAG, Agentic Workflows, and Machine Learning. If you love building intelligent AI agents that solve real-world business problems, this opportunity is for you. πŸ’‘ Mandatory Technical Skills πŸ€– Agentic AI & LLM Engineering LangGraph LangChain Multi-Agent Workflows Agent State & Memory Management Tool Calling & Function Calling Human-in-the-Loop Workflows 🧠 Generative AI & RAG Production RAG Solutions Vector Databases (Pinecone, Chroma, FAISS, OpenSearch) Embeddings & Semantic Search Context Engineering Retrieval Optimization πŸ’» Programming & Backend Python FastAPI REST APIs Microservices Architecture Async Programming ☁️ Cloud & DevOps AWS Amazon Bedrock Docker Kubernetes (Amazon EKS Preferred) Git & CI/CD Pipelines πŸ“Š AI Evaluation & Observability LangSmith RAGAS DeepEval Langfuse OpenTelemetry Token, Cost & Latency Monitoring πŸ€– Machine Learning Pandas NumPy Scikit-learn TensorFlow / PyTorch XGBoost / LightGBM Feature Engineering Model Deployment ⭐ Preferred Skills βœ” MCP (Model Context Protocol) βœ” AWS Strands Agents SDK βœ” Google Agent Development Kit (ADK) βœ” Prompt Engineering βœ” Prompt Guardrails βœ” Amazon Bedrock Guardrails βœ” Knowledge Graphs & Graph RAG βœ” Amazon Neptune βœ” LoRA / PEFT βœ” Quantization & Model Optimization βœ” Secure AI Engineering & OWASP Top 10 for LLM Applications πŸŽ“ Qualifications B.Tech / B.E. / Graduation in Computer Science or a related field Strong experience building and deploying production-grade AI/ML applications
tal saysdesign and deploy enterprise-scale generative ai applications, rag, and multi-agent workflows
ai-ml senior hybrid Bangalore pythonlangchainlanggraphfastapiaws
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Agentic AI Engineer Aarti Vohra Β· Treyansh
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