AI Agent Engineer

🗂 We’re Hiring: AI Agent Engineer 🕒 Employment Type: Full-Time 💼 Level: Entry-Level to Mid-Level We are seeking a motivated, innovative, and technically skilled AI Agent Engineer to join our growing AI engineering team. This role is ideal for individuals passionate about Generative AI, Large Language Models, autonomous agents, intelligent automation, and building AI systems capable of reasoning, using tools, and completing complex tasks. 🎯 Key Responsibilities • Design, develop, test, and deploy intelligent AI agents powered by Large Language Models. • Build multi-step agent workflows for planning, reasoning, decision-making, and task execution. • Integrate AI agents with APIs, databases, search systems, enterprise applications, and external tools. • Develop agent architectures using function calling, tool calling, structured outputs, and workflow orchestration. • Build Retrieval-Augmented Generation (RAG) systems and knowledge-based AI agents. • Design memory, context management, state management, and agent interaction mechanisms. • Develop and optimize prompts, system instructions, workflows, and agent behaviors. • Build AI agents capable of interacting with business systems and automating complex workflows. • Evaluate agent performance, accuracy, reliability, latency, scalability, and operational costs. • Develop testing and evaluation frameworks for AI agent applications. • Implement guardrails, validation, monitoring, error handling, and fallback mechanisms. • Troubleshoot agent behavior, tool execution, model outputs, and workflow failures. • Optimize AI agent systems for production performance and reliability. • Collaborate with LLM Engineers, Software Developers, Data Scientists, Product Managers, and DevOps teams. • Research emerging agentic AI frameworks, architectures, models, and industry best practices. • Maintain technical documentation covering agent architecture, workflows, tools, prompts, evaluations, and deployment processes. ✅ Requirements • Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related field is preferred. • Experience with LLMs, Generative AI, AI agents, NLP, machine learning, or software engineering is an advantage. • Strong programming skills in Python or another modern programming language. • Strong understanding of LLM concepts, APIs, prompt engineering, embeddings, and model inference. • Experience with agent frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, or similar technologies is an advantage. • Familiarity with RAG, vector databases, semantic search, embeddings, and knowledge retrieval systems. • Experience integrating APIs, databases, external tools, and enterprise systems with AI applications. • Understanding of REST APIs, Git, cloud platforms, databases, and software development practices. • Knowledge of AI evaluation, observability, guardrails, and responsible AI practices is a plus. • Strong analytical, debugging, experimentation, and problem-solving abilities. • Ability to design reliable workflows for complex, multi-step tasks. • Strong communication and collaboration skills. • Good written and verbal communication skills in English. • Strong interest in autonomous AI systems, agentic workflows, and emerging AI technologies. 🌟 What We Offer • Hands-on experience building real-world AI agents and autonomous AI systems. • Opportunities to work with LLMs, agent frameworks, RAG systems, vector databases, and AI infrastructure. • Exposure to intelligent automation, tool-using agents, multi-agent workflows, and enterprise AI applications. • Structured training and mentorship from experienced AI and software engineering professionals. • Career progression into Senior AI Agent Engineer, LLM Engineer, AI Engineer, AI Solutions Architect, or AI Technical Lead roles. • Opportunities to work on innovative AI products and intelligent automation projects. • Dynamic, innovative, and technology-driven working environment. • Continuous learning and professional development opportunities. • Competitive compensation with performance-based incentives.