AI Engineer
Hybrid / United StatesFull time
ApplyAbout the role
Job Title:
AI Engineer
Location:
Charlotte, NC
Interview:
Face-to-Face / In-Person
Employment Type:
Contract / Contract-to-Hire
Work Arrangement:
Hybrid / Onsite as required
Experience:
5+ Years Overall IT Experience; 3+ Years in AI/ML/GenAI
Visa Status:
USC, H1B, GC-EAD, H4-EAD only
Job Summary
We are seeking an experienced
AI Engineer
to design, develop, deploy, and support enterprise-grade Artificial Intelligence, Machine Learning, Generative AI, and Large Language Model (LLM) solutions.
The ideal candidate will have strong hands-on experience with
Python, Generative AI, RAG, LLMs, Azure OpenAI, Azure AI Search, vector databases, AI agents, document intelligence, REST APIs, and cloud-native application development
.
The candidate will work closely with engineering, architecture, data, security, and business teams to build scalable AI solutions that integrate enterprise data and applications.
Key Responsibilities
- Design, develop, test, deploy, and maintain production-grade AI/ML and Generative AI applications.
- Build LLM-powered applications using Azure OpenAI, OpenAI APIs, or other enterprise AI platforms.
- Design and implement Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge and document search.
- Develop AI-powered document processing, classification, extraction, summarization, and validation pipelines.
- Build intelligent AI agents using LangChain, LangGraph, Semantic Kernel, or similar frameworks.
- Implement agentic workflows including tool calling, orchestration, state management, context engineering, and structured outputs.
- Develop Python-based AI services, APIs, automation frameworks, and reusable components.
- Build and integrate REST APIs, microservices, and enterprise applications.
- Implement semantic, keyword, vector, and hybrid search capabilities.
- Develop embedding pipelines and integrate vector databases such as Pinecone, FAISS, Weaviate, ChromaDB, PostgreSQL/pgvector, or Azure AI Search.
- Perform prompt engineering, prompt evaluation, context optimization, and response-quality improvement.
- Implement document intelligence solutions using OCR, document extraction, classification, and entity recognition.
- Work with structured and unstructured enterprise data.
- Integrate AI solutions with SQL databases, APIs, data platforms, and enterprise applications.
- Develop model evaluation frameworks to measure accuracy, relevance, latency, cost, and reliability.
- Implement AI guardrails, security controls, monitoring, logging, and observability.
- Containerize AI applications using Docker and deploy them using Kubernetes/AKS or similar platforms.
- Participate in CI/CD implementation using Azure DevOps, GitHub Actions, Jenkins, or equivalent technologies.
- Troubleshoot production AI applications and improve performance and scalability.
- Collaborate with architects, developers, data engineers, cybersecurity teams, and business stakeholders.
- Participate in Agile/Scrum ceremonies, sprint planning, code reviews, and technical discussions.
- Create technical documentation covering architecture, implementation, APIs, AI workflows, and operational procedures.
Required Technical SkillsProgramming
- Strong hands-on experience with Python
- Python APIs and microservices
- FastAPI or Flask
- REST APIs
- JSON
- Pydantic
- Unit testing and debugging
- Git/GitHub
Generative AI / LLM
- Large Language Models (LLMs)
- Generative AI
- Prompt Engineering
- Context Engineering
- Structured Outputs
- Function Calling / Tool Calling
- AI Agents
- Agentic AI
- Multi-step AI workflows
- LLM evaluation
- AI guardrails
RAG & Enterprise Search
- Retrieval-Augmented Generation (RAG)
- Embeddings
- Semantic Search
- Vector Search
- Hybrid Search
- Keyword Search
- Query Rewriting
- Reranking
- Chunking strategies
- Metadata filtering
- Knowledge retrieval
AI / Cloud Platforms
Hands-on Experience With One Or More:
- Azure OpenAI
- Azure AI Search
- Azure AI Foundry
- Azure AI Document Intelligence
- Azure Cognitive Services
- AWS Bedrock
- OpenAI APIs
- Google Vertex AI
AI Frameworks
Experience With One Or More:
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- AutoGen
- CrewAI
Vector Databases
Experience With One Or More:
- Pinecone
- FAISS
- Weaviate
- ChromaDB
- Milvus
- PostgreSQL / pgvector
- Azure AI Search
Data & Databases
- SQL
- PostgreSQL
- SQL Server
- Oracle
- MongoDB
- Structured and unstructured data
- Data pipelines
- ETL/ELT concepts
Cloud & DevOps
- Microsoft Azure
- Docker
- Kubernetes / AKS
- Azure DevOps
- GitHub Actions
- CI/CD
- Application monitoring
- Logging and observability
Document Intelligence Experience
The Candidate Should Have Experience Developing Solutions For:
- PDF and document ingestion
- OCR processing
- Document classification
- Text extraction
- Entity extraction
- Metadata extraction
- Document summarization
- Document comparison
- Structured data extraction
- Validation workflows
- Intelligent document search
Experience with
Azure Document Intelligence, PyMuPDF, Tesseract OCR, or similar technologies
is a plus. Current Charlotte AI roles are also emphasizing document intelligence, OCR, RAG, and Azure AI Search.
AI Agent Experience
Candidates Should Understand Modern Agentic AI Architectures, Including:
- AI agents
- Tool calling
- Function calling
- Agent orchestration
- Planner/executor patterns
- Multi-agent workflows
- State management
- Memory/context management
- Structured responses
- Human-in-the-loop workflows
- Agent evaluation
- Guardrails and safety controls
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or related field.
- 5+ years of professional software/technology experience.
- 3+ years of hands-on AI/ML, Generative AI, Machine Learning, or AI application development experience.
- Strong Python development experience.
- Production experience building AI/LLM applications.
- Experience with RAG and vector/semantic search.
- Experience integrating AI solutions with APIs and enterprise systems.
- Strong understanding of software development lifecycle and Agile methodologies.
- Strong communication and problem-solving skills.
- Ability to work in a collaborative enterprise environment.
Preferred Qualifications
- Experience with financial services, banking, insurance, healthcare, or other regulated industries.
- Experience with enterprise document intelligence.
- Experience with knowledge graphs or graph databases.
- Experience with Azure Kubernetes Service (AKS).
- Experience with AI observability and LLMOps.
- Experience with model evaluation and quality metrics.
- Experience with NLP, NER, text classification, and information extraction.
- Experience with React/TypeScript or other frontend technologies is a plus.
- Experience with enterprise security, privacy, governance, and compliance.
Soft Skills
- Excellent verbal and written communication.
- Strong analytical and problem-solving skills.
- Ability to work independently and within Agile teams.
- Ability to communicate complex AI concepts to technical and non-technical stakeholders.
- Strong ownership and accountability.
- Ability to work in a face-to-face interview and onsite/hybrid work environment in Charlotte, NC.
Interview Process
Interview Type:
Face-to-Face / In-Person
Candidates Should Be Prepared For Technical Discussions Covering:
- Python
- Generative AI
- LLM architecture
- RAG
- Prompt Engineering
- Azure OpenAI
- Azure AI Search
- Vector databases
- AI Agents
- LangChain/LangGraph
- REST APIs
- Cloud architecture
- Kubernetes
- AI system design
- Real-world project experience
Work Authorization
Only The Following Work Authorization Statuses Will Be Considered:
- U.S. Citizen (USC)
- H1B
- Green Card EAD (GC-EAD)
- H4-EAD
Visa sponsorship is not available for this position.
Candidates must be able to provide valid documentation confirming authorization to work in the United States.
Location Requirement
Charlotte, NC
This position requires the candidate to be available for an
in-person/f2f interview
and to work onsite/hybrid in the Charlotte, NC area as required by the client.
Recruiter Submission Requirements
Please Submit:
- Updated Resume
- Candidate Full Name
- Current Location
- Phone Number
- Work Authorization
- Visa Expiration Date, if applicable
- Total IT Experience
- AI/ML Experience
- Python Experience
- RAG/GenAI Experience
- Azure Experience
- Expected Rate
- Availability for Face-to-Face Interview
- Availability to Start
Note:
Current Charlotte postings show strong demand for combinations of Python, Azure AI, RAG, vector search, document intelligence, agentic AI, and Kubernetes, making these useful core requirements for this opening.
Skills: genai,restapi,aiml,python,windows azure
