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Tier-1 brand, metro location, mid-level role, and broad GenAI skillset increase applicant competition.
Specialized GenAI modeling, orchestration, and vector search skills limit easy cross-industry transferability.
Explicit years plus mandatory GenAI toolchain, cloud AI ecosystems, and LLMOps requirements make filters highly strict.
Develop and deploy enterprise-grade Generative AI applications, APIs, and microservices with focus on LLM orchestration and Retrieval-Augmented Generation (RAG) pipelines.
Build multi-agent systems and autonomous workflows for automating complex business processes using orchestration frameworks.
Implement responsible AI practices including safety, content moderation, data privacy, performance evaluation, and monitor LLM production environments; collaborate with clients on PoCs to demonstrate GenAI capabilities.
4-7 years of software development experience with strong computer science fundamentals.
Proficiency in Python programming and experience developing RESTful/GraphQL APIs using frameworks like FastAPI, Flask, or Django.
Hands-on experience with at least one major cloud AI ecosystem (GCP Vertex AI, Azure OpenAI, or AWS Bedrock) and proficiency with SQL and NoSQL databases.
Education qualification: BE/BTech/MTech/MCA/MBA (full-time) in a relevant field.
Experienced in advanced frameworks such as LangChain, LlamaIndex, or LangGraph, and vector databases/search engines for semantic search applications.
Skilled in prompt engineering, embeddings, and designing complex system prompts for LLM applications.
Familiar with containerization (Docker), CI/CD pipelines, LLM monitoring tools, and preferably knowledge of fine-tuning models, graph databases, and UI prototyping frameworks.