AI Developer
Hptech Inc.
Dearborn, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Dearborn, United States of America
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Databases
Machine Learning
NoSQL
TensorFlow
Standard Sql
Search Technologies
Unstructured Data
Google Cloud Platform
Data Ingestion
PyTorch
Large Language Models
Prompt Engineering
Model Validation
Generative AI
GIT
Containerization
AI Platforms
Kubernetes
HuggingFace
REST
Data Pipelines
Docker
Job description
We are seeking a highly skilled AI Developer with hands-on experience in building, deploying, and optimizing Generative AI applications using Large Language Models (LLMs). The ideal candidate will have strong expertise in LangChain, LangGraph, Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and modern AI application architectures. You will work closely with product, engineering, and business teams to design and implement intelligent AI solutions that drive business value.
Requirements
Technical Skills
- Strong proficiency in Python programming.
- Hands-on experience with:
- Large Language Models (OpenAI, Anthropic, Llama, Gemini, Mistral, etc.)
- LangChain
- LangGraph
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- AI Agents and Agentic Workflows
- Experience with vector databases such as:
- Pinecone
- Weaviate
- Chroma
- FAISS
- Milvus
- Knowledge of embedding models and semantic search techniques.
- Experience integrating REST APIs and third-party AI services.
- Familiarity with model evaluation, hallucination mitigation, and AI quality assessment.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Understanding of containerization and deployment technologies:
- Docker
- Kubernetes
- Experience with Git and CI/CD pipelines.
Database & Data Skills
- Experience working with SQL and NoSQL databases.
- Understanding of data pipelines, document processing, and data ingestion workflows.
- Knowledge of structured and unstructured data management.
AI/ML Knowledge
- Understanding of machine learning fundamentals.
- Familiarity with NLP concepts and transformer architectures.
- Experience with frameworks such as:
- Hugging Face Transformers
- PyTorch
- TensorFlow (optional)