AI Engineer (Applied)
Core
Deploying AI models and agentic workflows into production to solve real-world business problems, specifically in data classification, operational agents, and LLM service implementation.
Role type
Applied AI Engineer (LLM & Agentic Systems)
Builds
Production AI agents, FastAPI services around LLM APIs, automated data classification pipelines, and observability tools.
Domain
Artificial Intelligence, Large Language Models (LLMs), MLOps, Cloud Infrastructure
Deliverable
production ML models | product features | infrastructure
Required skills
Python, LLM API integration, Prompt engineering, Model deployment, Data preprocessing, Feature engineering, Model evaluation, Cloud platforms, MLOps practices
Preferred skills
TensorFlow, PyDantic, Docker, Async API calls, Token budgeting, Anomaly detection
Technologies
Python, FastAPI, Docker, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, Azure, Claude, GPT-4, Falcon, Llama
Responsibilities
Implement automated data classification into pipelines, build production operational AI agents, define data contracts for the agentic platform, implement FastAPI services with versioned prompt templates, configure structured output and prompt versioning, establish observability and fallback logic for LLM calls, run quality evaluations against human reviewer samples.
Seniority
Mid-Senior, hands-on IC
