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Tier-1 brand, metro location, and mid-level GenAI demand create strong applicant competition.
Highly specialized LLM, Agentic AI, and vector-search expertise limits cross-industry transferability.
Explicit 4-8 years requirement plus specialized GenAI, LLM, and vector DB skills make filters strict.
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Design, develop, and maintain scalable Agentic AI applications using modern AI frameworks and orchestration technologies.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines, vector search, and AI-driven workflows leveraging Large Language Models (LLMs) and vector databases.
Collaborate with cross-functional teams to deliver AI-powered products and perform experimentation, testing, and performance optimization to ensure reliability and scalability.
4 to 8 years of relevant experience in software engineering and Generative AI application development.
Bachelor's degree in Computer Science, AI, Machine Learning, or related technical field, or equivalent work experience.
Proficient in Python programming including libraries such as NumPy, Pandas, FastAPI, Streamlit and experience with LLM APIs, Agentic AI frameworks, and vector databases like FAISS or Milvus.
Experience with design, development, and deployment of AI solutions using technologies such as LangGraph, LangChain, Google ADK, Phoenix, Guardrails, Mem0, or similar frameworks.
Experienced in building enterprise software AI applications focused on agent orchestration and Generative AI technologies at scale.
Comfortable working in a fast-paced, collaborative, and cross-functional environment driving innovation in AI and automation.
Strong in practical AI engineering with hands-on expertise in modern orchestration frameworks and advanced AI techniques for real-world business use cases.