AI ML Engineer with python
AI Engineer
Job Title: AI Engineer with python
Location: Onsite
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/GenAIVisa 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 Skills
- ProgrammingStrong hands-on experience with PythonPython APIs and microservices
- FastAPI or FlaskREST APIsJSONPydanticUnit testing and debugging
- Git/GitHubGenerative AI / LLMLarge Language Models (LLMs)
- Generative AIPrompt Engineering
- Context Engineering
- Structured Outputs
- Function Calling / Tool CallingAI Agents
- Agentic AIMulti-step AI workflowsLLM evaluationAI guardrailsRAG & Enterprise Search
- Retrieval-Augmented Generation (RAG)
Embeddings
Semantic SearchVector SearchHybrid Search
Keyword SearchQuery Rewriting
RerankingChunking strategies
Metadata filtering
Knowledge retrievalAI / Cloud Platforms
Hands-on Experience With One Or More:
Azure OpenAIAzure AI SearchAzure AI Foundry
Azure AI Document Intelligence
Azure Cognitive ServicesAWS Bedrock
OpenAI APIsGoogle Vertex AIAI Frameworks
Experience With One Or More:
LangChainLangGraphLlamaIndexSemantic KernelAutoGenCrewAIVector Databases
Experience With One Or More:
PineconeFAISSWeaviateChromaDBMilvusPostgreSQL / pgvector
Azure AI SearchData & DatabasesSQLPostgreSQLSQL ServerOracleMongoDBStructured and unstructured data
Data pipelinesETL/ELT concepts
Cloud & DevOpsMicrosoft AzureDockerKubernetes / AKSAzure DevOpsGitHub ActionsCI/CDApplication monitoring
Logging and observability
Document Intelligence Experience
The Candidate Should Have Experience Developing Solutions For:
PDF and document ingestionOCR 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 AILLM architectureRAGPrompt Engineering Azure OpenAIAzure AI SearchVector databasesAI AgentsLangChain/LangGraphREST APIsCloud architecture KubernetesAI system design Real-world project experience Work Authorization Only The Following Work Authorization Statuses Will Be Considered: U.S. Citizen (USC)H1BGreen Card EAD (GC-EAD)H4-EADVisa 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, NCThis 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 NumberEmailWork Authorization
- Visa Expiration Date, if applicable
- Total IT ExperienceAI/ML Experience
- Python ExperienceRAG/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: azure, gen, python, ai ml, interview, vpython, ai