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Tier-1 brand, metro location, mid-level GenAI role, broad skillset raise applicant competition.
Specialized GenAI and LLMOps skills are industry-transferable but require ML-specific experience.
Multiple mandatory technical skills, explicit years, and specialized LLM/LLMOps stack increase filtering strictness.
Develop and deploy enterprise-grade Generative AI applications, APIs, and microservices focused on advancing client solutions.
Optimize Retrieval-Augmented Generation (RAG) pipelines and build multi-agent systems to automate complex business processes leveraging LLMs and orchestration frameworks.
Implement Responsible AI practices including safety guidelines, content moderation, data privacy, and establish evaluation frameworks to monitor LLM performance in production.
4-7 years of software development experience with strong computer science fundamentals.
Proficient in Python programming and experienced in building 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 (Azure OpenAI Service), or AWS (Amazon Bedrock).
Bachelor's degree in Engineering (BE/BTech) or equivalent (MTech, MCA, MBA full-time).
Experienced in working with advanced Generative AI frameworks such as LangChain, LlamaIndex, or LangGraph and vector databases like Pinecone or Milvus.
Demonstrates expertise in prompt engineering, embeddings, and semantic search techniques applicable to enterprise AI solutions.
Able to manage AI model integration, security, and compliance within cloud environments, and perform CI/CD deployments with containerization (Docker) and LLM monitoring tools.