7Th Sky Tech
AI ML Engineer
Skills
13 days ago
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Important information
Contract type:
Permanent
Salary:
$124,800 – $141,440 / year
Location:
Palo Alto, CA, USA
Work mode:
Onsite
Published on:
9 October 2026
What they need
AI Engineer
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
Skills: ai ml,vpython,vector,python,java
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