About Anteriad We are not just another B2B solution provider. We're problem solvers. We believe that data is the key to unlocking effective solutions that span a range of marketing challenges - from customer acquisition to demand generation to account-based marketing. Data is at the core of everything we do. Our team works tirelessly to create powerful solutions that drive real results for our clients. Whether it's through innovative technology or deep analysis, we're committed to finding the best path to growth for every one of our customers.    What You’ll Do: Develop  LLM-powered agents  and  RAG pipelines  with tool use, multi-step reasoning, memory, and human-in-the-loop, using frameworks like LangChain, LangGraph, Mastra, etc., across Python or JavaScript/TypeScript Build, orchestrate, and optimize agentic AI workflows, coordinating multiple agents, tools, and steps with context and state management across multi-step tasks Leverage  AI-assisted development tools  (Claude, Cursor, Codex, GitHub Copilot, Lovable, etc.) across the development lifecycle to accelerate development and assist in code refactoring, debugging, test case generation, and documentation Manage code using  Git  and platforms such as  GitHub  or  Bitbucket , including versioning, pull requests, and code reviews Identify performance bottlenecks and reliability issues, using AI-driven insights to optimize applications Design, develop, and maintain scalable web applications, building responsive UIs with  React.js ,  Tailwind CSS , and modern component libraries on the frontend, and robust services with  Node.js/Express.js/FastAPI  on the backend Develop, integrate, and optimize  RESTful APIs , ensuring performance, scalability, and security best practices Work closely with product, design, and QA teams, clearly communicating ideas and adapting quickly to evolving requirements in an agile environment Debug, optimize, and enhance application performance and reliability   What You’ll Bring: Looking for candidates with 0-2 years of experience. Practical, hands-on exposure to  AI-powered development tools  (Claude, Cursor, Codex, GitHub Copilot, Lovable, etc.) for coding, testing, and documentation Solid understanding of how LLMs work (tokens, context windows, embeddings, limitations) and hands-on  prompt engineering  (zero/few-shot, chain-of-thought, JSON/function calling) Exposure to agentic AI concepts and at least one agent framework ( LangChain ,  LangGraph ,  Mastra , or similar), including tool use, memory and state management, and multi-step workflows Familiarity with  RAG  and integrating LLM APIs into applications Proficiency in  GitHub and Git-based workflows  (GitHub, Bitbucket, etc.). Experience in  React.js  and modern  JavaScript (ES6+ / TypeScript ), leveraging AI-assisted tools to build scalable and high-quality UI components Hands-on experience  with Node.js and Express.js , using AI tools to accelerate backend development, debugging, and optimization Experience working with  REST APIs  and API documentation tools Familiarity with databases such as  PostgreSQL/ MySQL/MongoDB , using AI tools for query optimization and troubleshooting.   Good to Have: Awareness of agent orchestration and MCP (Model Context Protocol) for connecting agents to tools and data Basic awareness of evaluating LLM outputs and risks such as hallucinations, guardrails, and prompt injection Exposure to vector databases (pgvector, Pinecone, Chroma, etc.) Awareness of observability tooling for LLM applications (LangSmith, Langfuse, etc.) Basic awareness of open-source models and tools for agentic AI development Familiarity with Python and FastAPI for building and serving AI/agent services Working knowledge of Java and Spring Boot / Spring MVC