Agentic AI FullStack Engineer python & React Angular Bangalore

Hi We are having an opening for Agentic AI Full-Stack Engineer -(python & React/ Angular ) Bangalore - bellandur, - hybrid job Working Days: Monday Friday Job Timing: Day shift Role Summary We are seeking an experienced Agentic AI Full-Stack Engineer to design, build, and scale intelligent AI platforms that transform enterprise knowledge into actionable insights and autonomous workflows. This role combines expertise in Agentic AI, Full-Stack Engineering, Knowledge Management, Information Extraction, Workflow Orchestration, and Enterprise System Integration . The ideal candidate will develop AI agents capable of reasoning, planning, retrieving information, using tools, collaborating with other agents, and executing multi-step business processes. The engineer will build solutions that ingest information from diverse sourcesincluding PDFs, Word documents, Excel files, HTML/web pages, emails, images, APIs, databases, and enterprise applications and convert them into structured knowledge repositories that power AI assistants, copilots, and autonomous business workflows. PositionAgentic AI Full-Stack Engineer QualificationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or related discipline.Number of post1Office LocationBangalore - bellandur, - hybrid job 3 days from office - onsite client location Job TypeFull Time GenderMale/FemaleIndustryIT Experience: 510 years of software engineering experience. 3+ years of experience building AI-powered applications. Interview process Total 3 Technical round 2 rounds evaluation with LV (we can plan to take this together based on panel availability) & 1 with clientSalary30 to 35 L p.a. Key Responsibilities Key Responsibilities Agentic AI Engineering Design and develop autonomous AI agents capable of reasoning, planning, task execution, and workflow orchestration. Build multi-agent systems that collaborate to solve complex business problems. Develop agent frameworks incorporating memory, tool usage, retrieval, decision-making, and human-in-the-loop controls. Implement agent evaluation, monitoring, governance, and safety guardrails. Design autonomous workflows for knowledge discovery, content processing, and enterprise process automation. Information Extraction & Knowledge Creation Build intelligent pipelines to extract information from: PDF documents Word documents Excel spreadsheets HTML/Web content Emails Images and scanned documents APIs Structured and unstructured databases Develop OCR, document intelligence, and content extraction capabilities. Extract entities, relationships, metadata, business rules, and domain knowledge from enterprise content. Transform unstructured content into machine-readable formats. Knowledge Base & Enterprise Search Engineering Design and develop enterprise knowledge platforms and searchable knowledge repositories. Build Retrieval-Augmented Generation (RAG) architectures and semantic search solutions. Create document ingestion, chunking, embedding, indexing, and retrieval pipelines. Develop vector-search and knowledge retrieval frameworks. Enable source attribution, traceability, explainability, and confidence scoring. Ensure continuous synchronization and enrichment of enterprise knowledge assets. Full-Stack Application Development Build modern AI-powered web applications and user experiences. Develop scalable backend services, APIs, and microservices. Create orchestration layers for agent lifecycle management. Implement authentication, authorization, observability, logging, and monitoring capabilities. Design reusable software components and enterprise integration frameworks. Enterprise Integration & Automation Integrate AI agents with enterprise platforms, databases, collaboration tools, content repositories, and business applications. Develop connectors and APIs to access information across multiple enterprise systems. Automate multi-step workflows involving document processing, knowledge retrieval, approvals, recommendations, and decision support. Ensure security, compliance, and governance requirements are met. Platform Engineering & Operations Deploy and manage AI solutions on cloud-native platforms. Implement MLOps and LLMOps best practices. Build CI/CD pipelines and automated testing frameworks. Monitor agent performance, retrieval quality, model behavior, reliability, and operational cost. Optimize solutions for enterprise-scale workloads. Strong programming skills in: Python JavaScript / TypeScript SQL Experience designing scalable distributed systems and enterprise applications. Strong understanding of API-driven architectures and microservices. Key Skills & Requirements Agentic AI Experience designing autonomous AI agents and multi-agent systems. Experience with agent orchestration frameworks. Hands-on experience with: Large Language Models (LLMs) Agentic AI architectures Retrieval-Augmented Generation (RAG) Tool Calling Prompt Engineering AI Evaluation Frameworks Knowledge Graphs Knowledge Engineering Experience building: Enterprise Search Platforms Knowledge Bases Knowledge Graphs Semantic Search Solutions Document Intelligence Platforms Cloud & Data Platforms Experience with: Vector Databases Graph Databases Search Engines Cloud Platforms (AWS, Azure, GCP) Container Technologies CI/CD Platforms Technical Skills Technical Skills Agentic AI & Generative AI Agentic AI Systems Multi-Agent Architectures LLM Integration RAG Prompt Engineering Semantic Search Tool Orchestration Knowledge Graphs AI Evaluation & Monitoring Information Extraction OCR Document Parsing Metadata Extraction Entity Extraction Relationship Extraction Content Classification Document Intelligence Multimodal AI Backend Development Python FastAPI / Flask REST APIs Microservices Event-Driven Architecture Frontend Development React Angular TypeScript Modern UI Frameworks Data & Knowledge Platforms Relational Databases NoSQL Databases Vector Databases Search Technologies Knowledge Repositories DevOps & Cloud AWS / Azure / GCP Docker Kubernetes CI/CD Monitoring & Observability JoiningImmediate / 15 Days Success Profile The successful candidate will: Build autonomous AI agents that can reason, plan, retrieve knowledge, and execute business tasks. Convert large volumes of enterprise content into trusted and searchable organizational knowledge. Develop scalable AI platforms that improve productivity, decision-making, and operational efficiency. Create reusable agentic capabilities that can be leveraged across multiple business functions. Balance innovation with enterprise-grade security, reliability, governance, and scalability. Deliver measurable business value through intelligent automation and knowledge-driven AI solutions.