Applied AI Engineer

Job Title: Applied AI Engineer

Location: Orlando, FL (Onsite)
Duration: Long-Term Contract

Job Summary

We are seeking a highly skilled Applied AI Engineer with strong hands-on experience in building production-grade AI applications using Large Language Models (LLMs), Agentic AI frameworks, and modern Python backend technologies. The ideal candidate should have experience designing and deploying scalable AI solutions, integrating enterprise APIs, implementing Retrieval-Augmented Generation (RAG), and working with vector databases and cloud-native deployments.

This role requires someone who can take AI solutions from proof-of-concept to production while collaborating with cross-functional engineering and product teams.

Key Responsibilities

• Design, develop, and deploy enterprise AI applications using LLMs and Generative AI technologies.
• Build intelligent AI agents using frameworks such as:
• LangChain
• AutoGen
• Semantic Kernel
• Integrate AI model APIs including:
• OpenAI
• Hugging Face
• Develop scalable backend services using:
• FastAPI
• Flask
• Django REST Framework
• Build and optimize RAG pipelines with embeddings, semantic search, and vector databases.
• Work with vector stores such as:
• Pinecone
• Weaviate
• FAISS
• Chroma
• Develop microservices-based architecture and asynchronous APIs.
• Containerize and deploy applications using:
• Docker
• Deploy AI workloads on cloud platforms:
• Amazon Web Services
• Microsoft Azure
• Google Cloud
• Support CI/CD implementation and production monitoring.

Required Skills

Must Have

Client is mainly looking for:

1. Strong Python Engineer

Need someone with 8+ years in Python backend development.

Must have:

• Python
• REST APIs
• Microservices
• Async Programming
• API Integrations

2. Real Generative AI Experience

Not just course/certification hands-on project experience with:

• LLM APIs
• Prompt engineering
• Model orchestration
• Multi-agent systems
• AI workflow automation

Keywords client wants:
OpenAI, Hugging Face, GPT, LLM, GenAI, Agentic AI

3. Agent Framework Experience (Very Important)

Candidate should have production experience in at least one:

LangChain OR AutoGen OR Semantic Kernel

This is one of the biggest screening factors.

4. RAG + Vector DB Experience (Critical)

Client wants candidates who have built:

• Document ingestion pipelines
• Embedding workflows
• Semantic retrieval
• Knowledge assistants/chatbots

Tools:
Pinecone, Weaviate, FAISS, Chroma, Milvus

5. Deployment / Production Experience

Need engineering candidates, not researchers.

Must know:

• Docker
• CI/CD
• Cloud deployment
• Production API deployment