Agentic AI Engineer

About the Role

Agentic AI Engineer We are looking for a highly curious and hands\-on **Agentic AI Engineer** to help us design, build, and deploy intelligent AI agents and automation systems. You will work on real\-world AI systems that can **reason, use tools, retrieve information, make decisions, execute multi\-step workflows, and interact with users and external systems**. This is a highly practical role for someone who wants to move beyond basic chatbots and learn how to build **production\-ready AI agents**. Key Responsibilities * Design and develop **AI agents and multi\-agent workflows**. * Build LLM\-powered applications using models such as GPT, Claude, Gemini, or open\-source LLMs. * Develop agent workflows involving **reasoning, planning, tool calling, memory, retrieval, and autonomous task execution**. * Integrate AI agents with APIs, databases, web services, internal tools, and third\-party applications. * Build **RAG (Retrieval\-Augmented Generation)** systems and knowledge bases. * Work with vector databases and embedding systems. * Develop structured prompts, tool definitions, agent instructions, and evaluation frameworks. * Experiment with agent frameworks such as **LangChain, LangGraph, CrewAI, AutoGen, or equivalent technologies**. * Build AI\-powered automation for research, analysis, operations, customer support, and internal workflows. * Evaluate agent performance, hallucinations, reliability, latency, and cost. * Debug and improve AI workflows based on real\-world performance. * Work closely with product and engineering teams to convert business problems into AI solutions. Skills Required **Programming** * Strong Python programming skills. * Good understanding of APIs, JSON, REST, authentication, and web services. * Basic knowledge of Git/GitHub. * Familiarity with databases and SQL. **AI / LLM** * Understanding of LLMs and generative AI. * Experience with OpenAI, Anthropic, Google, or open\-source model APIs. * Understanding of prompt engineering and structured outputs. * Familiarity with function/tool calling. * Understanding of embeddings and vector search. * Basic knowledge of RAG architectures. * Understanding of AI agents, workflows, planning, memory, and tool use. **Agentic AI** * Experience with one or more agent frameworks such as: * LangChain * LangGraph * CrewAI * AutoGen * Semantic Kernel * OpenAI Agents SDK * Equivalent frameworks **Engineering** * Ability to build and debug working prototypes. * Understanding of asynchronous programming is a plus. * Familiarity with Docker and cloud platforms is a plus. * Experience deploying applications/API services is a plus. What We Look For We care more about **what you have built than what courses you have completed.** Strong candidates may have built: * AI agents * Research agents * Autonomous workflows * RAG applications * AI assistants * Multi\-agent systems * Browser/API automation * AI\-powered SaaS products * LLM\-based developer tools * Personal AI automation projects Ideal Candidate You are someone who: * Loves experimenting with new AI technologies. * Can turn an idea into a working prototype quickly. * Enjoys solving ambiguous problems. * Understands that LLMs can be unreliable and knows how to build around those limitations. * Thinks about **accuracy, latency, cost, security, and scalability**, not just whether a demo works. * Can read documentation and learn unfamiliar technologies independently. * Is comfortable breaking complex problems into smaller workflows. * Has a strong engineering mindset and takes ownership. Bonus Skills Experience with: * LangGraph * MCP / Model Context Protocol * Function calling / tool use * Agent evaluation * LLM observability * Fine\-tuning / LoRA * PostgreSQL * Redis * Pinecone / Weaviate / Qdrant / Chroma * FastAPI * Docker * AWS / GCP / Azure * React / Next.js * Computer\-use agents * Browser automation * Voice AI * Multimodal AI is a strong advantage. What You'll Learn You will gain hands\-on experience building **real agentic AI systems**, including: **LLMs → RAG → Tools → Agents → Multi\-Agent Workflows → Evaluation → Production Deployment** You will work closely with the product and technology team and have the opportunity to take AI systems from **idea → prototype → deployment**. Who Can Apply Students and recent graduates from: **Computer Science, AI/ML, Data Science, Software Engineering, Electronics, Mathematics, or related fields.** Candidates with strong personal AI projects are encouraged to apply even without formal AI/ML experience. Important **We are looking for builders, not certificate collectors.** If you have built an interesting AI agent, automation, RAG system, LLM application, GitHub project, or experimental AI product, **include it with your application.** Pay: ₹473,984\.98 \- ₹1,759,619\.55 per year Benefits: * Flexible schedule * Work from home Experience: * agentic: 1 year (Required) Work Location: Remote