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Strong PwC brand, metro locations, mid-level generalist GenAI skillset creates high applicant competition.
Core GenAI engineering skills are transferable, but enterprise systems and consulting domain exposure prefer similar industries.
Explicit 5+ years requirement plus mandatory GenAI/LLM and backend tech stacks increases filter strictness.
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Design, build, test, and deploy Generative AI applications including enterprise chatbots, document intelligence, and AI-led automation.
Develop and integrate GenAI features using LLM APIs, prompt engineering, vector databases, and agentic frameworks with backend systems and enterprise knowledge sources.
Build backend services and APIs for LLM orchestration, semantic search, document ingestion, evaluation, and agent execution while ensuring secure coding and observability.
5+ years of total work experience with at least 1+ year in GenAI/LLM ecosystems.
Educational Qualification: B.E./B.Tech/MCA/M.E/M.Tech/MBA/PGDM in full-time regular mode without backlogs.
Hands-on experience with LLM APIs, prompt engineering, RAG pipelines, vector databases, and frameworks like LangChain, LangGraph, CrewAI, or LlamaIndex.
Proficiency in backend development using Python, FastAPI, Node.js, REST APIs, and working knowledge of SQL/NoSQL databases and cloud AI platforms.
Experienced technologist capable of end-to-end GenAI application development including agentic AI workflows and integration with enterprise systems.
Skilled in building scalable backend services with secure coding practices and observability for AI deployments.
Familiar with rapidly evolving GenAI tools and frameworks, comfortable working in agile teams, and adept at handling complex AI evaluation and production deployment challenges.