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Strong brand, mid-level sought-after GenAI role in metros increases candidate competition.
GenAI technical skills are transferable across industries, but LLM-specific experience remains necessary.
Explicit 5+ years plus mandatory GenAI frameworks and backend skills make shortlisting stringent.
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Design, build, test, and deploy generative AI applications involving LLM APIs, semantic search, vector databases, prompt engineering, and agentic frameworks.
Develop and integrate AI features like enterprise chatbots, document intelligence, automation agents, and business process automation into backend systems and APIs.
Build and maintain document ingestion pipelines, implement semantic and hybrid search, support retrieval optimization, and develop backend services with secure coding and observability practices.
5+ years of overall work experience with at least 1+ year in GenAI/LLM ecosystems.
Bachelor's degree in Engineering (B.E./B.Tech), MCA, M.E., M.Tech, MBA, or PGDM in regular full-time mode without course extension due to backlogs.
Hands-on experience required with LLM APIs, prompt engineering, embeddings, RAG, semantic search, vector databases, LangChain or equivalent frameworks, Python, FastAPI, Node.js, REST APIs, SQL/NoSQL databases, and Redis caching.
Working knowledge of cloud AI platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI, etc.), document processing, evaluation tools (LangSmith, Langfuse), and basic understanding of security and responsible AI practices.
Experienced in developing complex GenAI applications using a broad set of LLM tools, frameworks, and backend technologies, indicating strong technical depth in AI and software development.
Comfortable working in agile teams, collaborating cross-functionally to integrate AI capabilities within enterprise environments and backend systems.
Familiar with operationalizing AI solutions including testing, evaluation, security controls, and observability in production settings, showing an end-to-end delivery orientation.