Role :  AI Developer - Agentic AI Exp: 2-3 Years Work Mode: 12- 10 pm, Onsite( Mohali, Punjab) Job Role & Responsibilities * Design, develop, and deploy Agentic AI systems capable of autonomous task execution by integrating reasoning, memory, and tool use to enable intelligent behavior across complex, multi-step workflows. * Architect intelligent agents that can dynamically interact with APIs, data sources, and third-party tools to accomplish diverse objectives with minimal human intervention. * Optimize performance of agentic frameworks by enhancing model accuracy, minimizing response latency, and ensuring scalability and reliability in real-world applications. * Develop reusable, testable, and production-grade code , adhering to best practices in software engineering and modern AI development workflows. * Collaborate with cross-functional teams , including product managers, designers, and backend engineers, to convert business requirements into modular agent behaviors. * Integrate Retrieval-Augmented Generation (RAG) , advanced NLP techniques, and knowledge graph structures to improve decision-making and contextual awareness of agents. * Conduct rigorous profiling, debugging, and performance testing of agent workflows to identify bottlenecks and improve runtime efficiency. * Write and maintain comprehensive unit, integration, and regression tests to validate agent functionality and ensure robust system performance. * Continuously enhance codebases , refactor existing modules, and adopt new design patterns to accommodate evolving agentic capabilities and improve maintainability. * Implement secure, fault-tolerant, and privacy-compliant designs to ensure that deployed agentic systems meet enterprise-grade reliability and data protection standards. Qualification Required: Bachelor's degree in computer science , or related field. Specialization or Certification in AI or ML is a plus. Technical Expertise: * 2+ years of hands-on experience in AI/ML/DL projects, with a strong emphasis on Natural Language Processing (NLP) , Named Entity Recognition (NER) , and Text Analytics . * Proven ability to design and deploy Agentic AI systems -autonomous, goal-oriented agents that exhibit reasoning, memory retention, tool use, and execution of multi-step tasks. * Practical expertise in agent architecture , task decomposition, and seamless integration with external APIs, databases, and tools to enhance agent capabilities. * Skilled in agent prompting strategies , including dynamic prompt chaining and context management, to guide language models through intelligent decision-making workflows. * Experience with Retrieval-Augmented Generation (RAG) pipelines and generative AI , with a strong focus on optimizing NLP models for low-latency, high-accuracy production use. * Solid foundation in deep learning methods , recommendation engines, and AI applications within HR  or similar domains. * Exposure to Reinforcement Learning (RL) frameworks and holds relevant certifications or specializations in Artificial Intelligence , showcasing continuous learning and depth in the field. Minimum skills we look for: Skills & Expertise (with Agentic AI focus) * Proven experience in building Agentic AI systems , including autonomous agents capable of multi-step reasoning, memory management, and tool use. * Expertise in agent design patterns , task decomposition , dynamic planning, and decision-making logic using LLMs. * Skilled in integrating multi-agent coordination , goal-setting, and feedback loops to create adaptive, evolving agent behavior. * Strong command over prompt engineering , contextual memory structuring , and tool calling mechanisms within LLM-powered agent workflows. * Proficiency in managing agent memory (short-term, long-term, episodic) using vector databases and custom memory stores. * Ability to build autonomous task execution pipelines with minimal human input, combining language models, APIs, and third-party tools. * Experience with frameworks and orchestration for agent behavior tracing, logging, and failure recovery . Tools & Technologies – Agentic AI * Agentic Frameworks : LangChain, CrewAI, AutoGen, AutoGPT, BabyAGI – for building, managing, and orchestrating intelligent agents. * LLM APIs : OpenAI (GPT-4/3.5), Anthropic (Claude), Cohere, Hugging Face Transformers. * Memory & Vector Databases : FAISS, Weaviate, Pinecone, Chroma – for embedding-based agent memory and contextual retrieval. * Prompt Management Tools : PromptLayer, LangSmith – for testing, evaluating, and refining agent prompts and traces. * RAG & Context Enrichment : LangChain RAG pipelines, Haystack, Milvus. * Autonomy Infrastructure : Docker, FastAPI, Redis, Celery – for building scalable agent runtimes. * Observability : OpenTelemetry, Langfuse (or similar) for tracing agent decisions, failures, and success metrics. * Testing Agentic Behavior : Integration with PyTest + mock APIs/tools to validate autonomous decision logic and fallback strategies.