Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Niche LLM specialization reduces pool, but general AI title and broad backend/frontend skills increase applicant density.
Core LLM, prompt engineering, and API skills are highly transferable across industries.
Many mandatory LLM, vector DB, cloud, and programming skills imply moderate shortlisting stringency.
Design, build, and deploy Large Language Model (LLM) powered applications including chatbots, copilots, agents, and Retrieval-Augmented Generation (RAG) pipelines.
Develop and optimize prompt engineering strategies and fine-tune LLMs using techniques like LoRA/QLoRA and RLHF for production use cases.
Build backend services/APIs in Java and Python to support scalable LLM applications and collaborate on React front-end for AI feature delivery.
Bachelor's or Master's degree in Computer Science, Machine Learning, or related field (or equivalent practical experience).
Strong programming skills in Java and Python required.
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and open-source LLMs (Llama, Mistral, etc.).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and maintaining advanced LLM systems including prompt engineering, RAG architectures, vector databases, and agentic AI workflows.
Familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph), cloud platforms (AWS/GCP/Azure), containerization (Docker/Kubernetes), and AI-serving backend APIs (REST/gRPC).
Competent in fine-tuning LLMs and implementing guardrails, content filtering, and responsible AI practices with a strong understanding of transformer models.