AI Software Engineer

Responsibilities

• Design, develop, and deploy AI-powered software systems at great speeds using modern programming frameworks and AI tooling such as Antigravity, Cursor, and Claude Code.
• Build, orchestrate, and maintain agent-based AI systems using LangGraph, AutoGen, and related multi-agent frameworks.
• Implement multi-agent workflows where specialized agents collaborate for reasoning, planning, tool use, and task execution.
• Develop and optimize LLM pipelines, including prompt and context engineering, memory, tool calling, and state management.
• Design and integrate retrieval-augmented generation (RAG) systems using embeddings and vector databases.
• Build backend services and RESTful APIs to support AI inference, agent coordination, and workflow execution.
• Ensure AI systems meet production standards for scalability, performance, security, and reliability.
• Collaborate with product, data, and engineering teams to translate business problems into agentic AI solutions.
• Conduct code reviews and enforce best practices across AI and software engineering.
• Stay current with advancements in agentic AI, orchestration frameworks, and LLM infrastructure.
  
  

• 1-4 years of experience in software engineering with hands-on exposure to AI-driven systems.
• Strong algorithmic thinking, coding skills, problem-solving skills, and systems-level reasoning.
• Practical experience with Large Language Models (LLMs) and AI application development.
• Hands-on experience with LangGraph or similar agent orchestration frameworks.
• Understanding of multi-agent architectures, agent communication patterns, and task coordination.
• Experience designing RAG pipelines, embeddings, and vector search workflows.
• Solid understanding of SDLC, system design, and scalable backend architectures.
• Experience building and integrating RESTful APIs for AI and non-AI services.
• Familiarity with AI developer productivity tools such as Cursor, Anti Gravity, Claude Compose, or equivalent platforms.
• Strong communication and collaboration skills in fast-moving, experimental environments.
• Experience building and deploying production-grade applications end-to-end quickly using Agentic AI is mandatory.
• Experience with open-source AI models and AI inference engines is a plus but not mandatory.