Position : Agentic AI Full-Stack Engineer

Qualification : Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or related discipline.

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 : 1. PDF documents 2. Word documents 3. Excel spreadsheets 4. HTML/Web content 5. Emails 6. Images and scanned documents 7. APIs 8. 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.

Technical Requirements :

- Strong programming skills in Python, JavaScript/TypeScript, and 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 : 1. Large Language Models (LLMs) 2. Agentic AI architectures 3. Retrieval-Augmented Generation (RAG) 4. Tool Calling 5. Prompt Engineering 6. AI Evaluation Frameworks 7. Knowledge Graphs.

Knowledge Engineering :

- Experience building : 1. Enterprise Search Platforms 2. Knowledge Bases 3. Knowledge Graphs 4. Semantic Search Solutions 5. Document Intelligence Platforms.

Cloud & Data Platforms :

- Experience with : 1. Vector Databases 2. Graph Databases 3. Search Engines 4. Cloud Platforms (AWS, Azure, GCP) 5. Container Technologies 6. CI/CD Platforms.

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.

Joining : Immediate or 15 Days.

Success Profile :

- 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.