Job
Description
As an AI Developer specializing in Agentic AI, you will be responsible for designing, developing, and deploying Agentic AI systems that exhibit autonomous task execution capabilities through the integration of reasoning, memory, and tool use. Your role will involve architecting intelligent agents that can dynamically interact with APIs, data sources, and third-party tools to achieve diverse objectives with minimal human intervention. It will also be essential to optimize the performance of agentic frameworks by enhancing model accuracy, minimizing response latency, and ensuring scalability and reliability in real-world applications. Collaborating with cross-functional teams, including product managers, designers, and backend engineers, will be a key aspect of your job to convert business requirements into modular agent behaviors. You will be expected to integrate advanced NLP techniques, such as Retrieval-Augmented Generation (RAG), and knowledge graph structures to enhance decision-making and contextual awareness of agents. Rigorous profiling, debugging, and performance testing of agent workflows will be necessary to identify bottlenecks and improve runtime efficiency. In terms of qualifications, a Bachelor's degree in computer science or a related field is required, with specialization or certification in AI or ML being a plus. The ideal candidate will have at least 2 years of hands-on experience in AI/ML/DL projects, with a strong emphasis on NLP, NER, and text analytics. Practical expertise in agent architecture, task decomposition, and integration with external APIs, databases, and tools will be essential. Experience with RAG pipelines, generative AI, deep learning methods, recommendation engines, and AI applications within HR or similar domains is highly desirable. Key skills and expertise we look for in a candidate include proven experience in building Agentic AI systems, designing autonomous agents capable of multi-step reasoning, memory management, and tool use. Proficiency in agent design patterns, task decomposition, dynamic planning, and decision-making logic will be crucial, along with the ability to integrate multi-agent coordination, goal-setting, and feedback loops to create adaptive agent behavior. Strong command over prompt engineering, contextual memory structuring, and tool calling mechanisms within LLM-powered agent workflows is also required. Familiarity with tools and technologies such as LangChain, CrewAI, AutoGen, AutoGPT, BabyAGI for building intelligent agents, as well as LLM APIs like OpenAI (GPT-4/3.5), Anthropic (Claude), Cohere, Hugging Face Transformers is beneficial. Experience with memory and vector databases, prompt management tools, RAG pipelines, autonomy infrastructure tools, observability tools, and testing frameworks for agentic behavior will be advantageous in this role. If you possess the necessary technical expertise and skills in Agentic AI development, this role offers an exciting opportunity to work on cutting-edge AI systems and contribute to the advancement of intelligent agent technology.,