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About the role
As a Software Engineer for AI Agents & Automation, you will play a crucial role in the AI revolution by designing and developing AI agents that automate manual workflows, enhance product features with intelligence, and lead the evolution of products into the AI era. Your responsibilities will include: - Designing, building, and deploying AI agents to automate manual, repetitive, or complex tasks - Working with LLM APIs such as OpenAI, Anthropic, Gemini, or open-source models to create intelligent features - Developing agentic pipelines using frameworks like LangChain, LangGraph, CrewAI, or AutoGen - Integrating AI agents into existing product workflows to streamline manual processes - Building tool-use and function-calling capabilities for agents to interact with APIs, databases, and systems - Upgrading existing product features by incorporating AI-powered enhancements - Evaluating agent performance, enhancing prompt engineering, and ensuring reliability - Collaborating with product and research teams to identify automation opportunities - Writing clean, testable, and well-documented code for seamless collaboration Qualifications required for this role include: - Education: B.Tech/M.Tech in Computer Science, IT, or a related field - Experience: 12 years of hands-on software development experience - Programming: Strong proficiency in Python as the primary language for agent development - AI/ML Awareness: Working knowledge of LLMs, prompt engineering, and AI APIs - Agent Frameworks: Hands-on exposure to at least one framework like LangChain, CrewAI, AutoGen, or LangGraph - APIs & Integration: Comfortable building and consuming REST APIs to connect agents with external systems - CS Fundamentals: Solid grasp of data structures, algorithms, and software design principles - Version Control: Proficient with Git for branching, pull requests, and code reviews Desirable skills that would be considered a strong plus include experience with RAG Pipelines, Open-Source LLMs, Multi-Agent Systems, Backend Development with FastAPI or Flask, Cloud Platforms knowledge (AWS/GCP/Azure), Containerization with Docker, Databases (SQL/NoSQL and vector stores), Evaluation & Observability tools like LangSmith or Weights & Biases, and a GitHub Presence with personal projects or contributions to open-source AI/agent tooling. If you have built or experimented with AI agents, chatbots, or LLM-powered tools, are comfortable with ambiguity and iteration in AI system development, seek to understand the behavior of agents, and aspire to shape AI features in products, then this role is tailored for you. Feel free to share a GitHub repo, demo, or write-up of an AI agent or LLM project you have worked on as a bonus. As a Software Engineer for AI Agents & Automation, you will play a crucial role in the AI revolution by designing and developing AI agents that automate manual workflows, enhance product features with intelligence, and lead the evolution of products into the AI era. Your responsibilities will include: - Designing, building, and deploying AI agents to automate manual, repetitive, or complex tasks - Working with LLM APIs such as OpenAI, Anthropic, Gemini, or open-source models to create intelligent features - Developing agentic pipelines using frameworks like LangChain, LangGraph, CrewAI, or AutoGen - Integrating AI agents into existing product workflows to streamline manual processes - Building tool-use and function-calling capabilities for agents to interact with APIs, databases, and systems - Upgrading existing product features by incorporating AI-powered enhancements - Evaluating agent performance, enhancing prompt engineering, and ensuring reliability - Collaborating with product and research teams to identify automation opportunities - Writing clean, testable, and well-documented code for seamless collaboration Qualifications required for this role include: - Education: B.Tech/M.Tech in Computer Science, IT, or a related field - Experience: 12 years of hands-on software development experience - Programming: Strong proficiency in Python as the primary language for agent development - AI/ML Awareness: Working knowledge of LLMs, prompt engineering, and AI APIs - Agent Frameworks: Hands-on exposure to at least one framework like LangChain, CrewAI, AutoGen, or LangGraph - APIs & Integration: Comfortable building and consuming REST APIs to connect agents with external systems - CS Fundamentals: Solid grasp of data structures, algorithms, and software design principles - Version Control: Proficient with Git for branching, pull requests, and code reviews Desirable skills that would be considered a strong plus include experience with RAG Pipelines, Open-Source LLMs, Multi-Agent Systems, Backend Development with FastAPI or Flask, Cloud Platforms knowledge (AWS/GCP/Azure), Containerization with Docker, Databases (SQL/NoSQL and vector stores), Evaluation & Observability tools like LangSmith or Weights & Biases, and a GitHub Prese
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