Senior Generative Ai Developer

3 weeks ago

Vellore, India Whatjobs IN C2 Full time

Job Title: Agentic AI Developer Experience: 4–6 Years Location: Remote Employment Type: Contract Job Summary We are seeking a highly skilled Agentic AI Developer with a strong background in engineering and hands-on experience in building, orchestrating, and deploying intelligent AI agents. The ideal candidate will have deep expertise in Python-based Generative AI (GenAI) development, multi-agent frameworks , and LLM integrations to design autonomous, goal-driven AI systems capable of reasoning, planning, and dynamic tool usage. Key Responsibilities Design, develop, and deploy agentic AI architectures leveraging multi-agent frameworks and LLMs. Build autonomous, reasoning-based AI agents capable of tool use, contextual data retrieval, and adaptive decision-making. Implement and orchestrate AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI . Integrate vector databases (Pinecone, FAISS, Weaviate) for efficient context management and semantic knowledge retrieval. Apply prompt engineering, fine-tuning, and context chaining to optimize model performance. Collaborate with cross-functional teams to deliver production-ready AI pipelines and microservices . Develop and integrate APIs and event-driven architectures for LLM operations within cloud environments (AWS, Azure, or GCP ). Stay abreast of the latest advancements in autonomous AI agents , GenAI frameworks , and LLM orchestration ecosystems . Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering , or a related field. 4–6 years of experience in AI/ML or software engineering , with a focus on LLM-driven applications . Strong proficiency in Python , with hands-on experience using LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI . Proven expertise in agentic workflows, tool-using agents, or multi-agent orchestration systems . Experience working with vector databases (Pinecone, FAISS, Weaviate) and knowledge retrieval mechanisms. Proficiency with OpenAI, Anthropic , or open-source LLMs, including prompt tuning and optimization techniques. Familiarity with API integration, event-driven design patterns , and cloud platforms (AWS preferred). Strong analytical, problem-solving, and communication skills . Nice to Have Experience with RAG (Retrieval-Augmented Generation) pipelines and memory-enabled agent architectures . Familiarity with AI observability tools and LLM evaluation frameworks . Contributions to open-source AI projects or research in the field of autonomous agents.

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