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Protocol Intelligence
Data-driven signals on your job's competitivenessRemote mid-level GenAI role with broad LLM requirements, metro targeting, and popular title yields high competition.
LLM engineering skills are broadly transferable, but agentic systems and gaming context create moderate domain specificity.
Explicit 3–6 years plus many mandatory LLM, deployment, and cloud skills implies high filtering.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy generative AI and conversational AI solutions using LLMs and agentic workflows.
Build scalable and production-ready AI pipelines and APIs (FastAPI/Flask) to serve AI models impacting millions of users.
Collaborate with data engineers for dataset preprocessing and optimize AI model performance aligned with business goals.
Minimum Requirements
3 to 6 years of professional experience in ML/AI with focus on modern LLM implementations.
Bachelor's, Master's, or PhD in Computer Science, Data Science, or related field.
Strong proficiency in Python and experience with AI/LLM libraries (e.g., transformers, vLLM, accelerate, PEFT/LoRA).
Experience building and deploying AI model serving APIs using FastAPI or Flask.
Ideal Candidate Profile
Experienced in implementing AI solutions with modern orchestration frameworks (e.g., LangChain, LlamaIndex) and agentic AI systems (e.g., LangGraph, AutoGen).
Hands-on with advanced AI tools including Google AI SDK, OpenAI SDK, vector DBs, RAG pipelines, and cloud ML deployment (AWS/Azure/GCP).
Skilled in fine-tuning deep learning models (TensorFlow/PyTorch) and deploying scalable production-level AI workflows integrating multi-agent orchestration.