Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Metro location and broad technical skillset increase applicant density, while niche LLM expertise tempers it.
LLM and NLP expertise is transferable, but healthcare reimbursement domain knowledge raises fit sensitivity moderately.
Multiple mandatory technical skills (LLMs, vector DBs, Java/Python, cloud, Docker/Kubernetes) enforce strict screening.
Design, build, and deploy LLM-powered AI applications including chatbots, RAG systems, and agentic workflows.
Develop and optimize prompt engineering strategies and maintain retrieval-augmented generation pipelines using vector databases.
Build and manage backend services in Java/Python at scale, implement evaluation frameworks, and enforce responsible AI guardrails and monitoring.
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.
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini) and open-source LLMs, plus practical experience in prompt engineering and RAG architecture.
Experience with vector databases, LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex), REST/gRPC APIs, and cloud platforms (AWS/GCP/Azure) with containerization (Docker/Kubernetes).
Experienced in deploying and fine-tuning state-of-the-art LLMs including open-source models using methods like LoRA/QLoRA, instruction tuning, and RLHF.
Capability to handle full-stack LLM features including backend API services and collaboration or contribution in React front-end integration.
Familiar with multi-agent AI workflows, LLM evaluation tools, responsible AI safeguards, and MLOps/LLMOps practices for model/versioning/observability in fast-evolving AI landscapes.