Applied AI Engineer

Job Description

Role Overview:

An Applied AI Engineer develops and integrates AI models into real-world applications to solve business and customer problems.

Key Responsibilities:

Build and deploy AI/ML and Generative AI applications.
Integrate LLMs and AI APIs into products.
Develop RAG, AI agents, and intelligent automation solutions.
Work with prompt engineering, embeddings, and vector databases.
Build APIs and backend services for AI applications.
Test and improve AI model accuracy, performance, and reliability.
Work with data scientists, software engineers, and product teams.
Deploy AI solutions to cloud/production environments.
Monitor AI applications and optimize cost, latency, and quality.

Required Skills:
Python
AI/ML fundamentals
LLMs & Generative AI
Prompt Engineering
RAG & Embeddings
Vector Databases
AI Agents / Tool Calling
REST APIs / FastAPI
SQL & basic data processing
Git
AWS / Azure / GCP
Docker — good to have
Good to Have
LangChain / LangGraph
OpenAI / Anthropic / Gemini APIs
MLflow
Kubernetes
AI evaluation & observability

Experience:
Usually 2–5+ years in AI/ML, Software Engineering, Data Science, or related fields.