Agentic AI Developer
New
W
Weekday AIGenerative AI
Location: IndiaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3–6 years of overall experience in software development, AI engineering, or backend development. Min Experience: 3+ years
- Required Skills
- PythonRESTful APIsPrompt EngineeringLangChain
Requirements
- Have 3–6 years of overall experience in software development, AI engineering, or backend development; the posting also states a minimum of 3+ years.
- Have strong Python programming experience and hands-on expertise building backend applications and AI solutions.
- Understand LLM capabilities, limitations, and practical applications.
- Have hands-on LangChain experience developing LLM-powered applications, chains, tools, and workflows.
- Understand prompt engineering, function calling, embeddings, and context management.
- Have experience building and integrating AI-powered applications using APIs and external data sources.
- Demonstrate hands-on experience developing LLM-based applications and AI-powered solutions.
- Have a strong understanding of modern AI architectures and agentic AI technologies.
- A bachelor's degree in Computer Science, Engineering, or a related technical discipline is preferred.
- OpenAI and Azure OpenAI API experience is listed as good to have.
- Experience with LangGraph, CrewAI, AutoGen, or similar agent orchestration frameworks is listed as good to have.
- Knowledge of RAG architectures and vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS is listed as good to have.
Responsibilities
- Design, develop, and deploy autonomous AI agents that perform complex tasks, reason, plan, and make decisions.
- Build LLM-powered applications using Python, LangChain, and other AI frameworks.
- Develop agentic workflows using LangGraph, CrewAI, or similar orchestration tools.
- Implement RAG pipelines using enterprise knowledge bases.
- Design multi-agent systems in which agents collaborate to accomplish complex tasks.
- Integrate LLMs with external APIs, databases, enterprise applications, and third-party services.
- Explore and implement MCP integrations connecting agents with external tools, data sources, and services.
- Optimize prompts, model performance, response accuracy, latency, and token consumption.
- Develop scalable backend services and REST APIs for AI-powered applications.
- Evaluate, test, debug, and improve agent performance, reliability, and security.
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