AI Engineer
Las Vegas, NV · On-site
$60 - $70/hr
Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, or Milvus) * Prompt Engineering * REST APIs * Git & CI/CD * SQL / NoSQL databases * Docker * Cloud Platform (AWS/Azure/GCP)
New
Quick apply
AI Engineer
Las Vegas, NV · On-site
$60 - $70/hr
Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, or Milvus) * Prompt Engineering * REST APIs * Git & CI/CD * SQL / NoSQL databases * Docker * Cloud Platform (AWS/Azure/GCP)
New
AI Engineer
Las Vegas, NV · On-site
$60 - $70/hr
Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, or Milvus) * Prompt Engineering * REST APIs * Git & CI/CD * SQL / NoSQL databases * Docker * Cloud Platform (AWS/Azure/GCP)
New
Quick apply
AI Engineer
Las Vegas, NV · On-site
$60 - $70/hr
Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, or Milvus) * Prompt Engineering * REST APIs * Git & CI/CD * SQL / NoSQL databases * Docker * Cloud Platform (AWS/Azure/GCP)
New
Senior Engineer - AI Strategy and Digital Automation
Las Vegas, NV · On-site
$99K - $137K/yr
Proficiency with vector databases (Vertex AI Vector Search, Pinecone) and agent orchestration frameworks (LangGraph, Google ADK). Minimum Qualifications: * Experience designing Context Graphs or ...
Senior Engineer - AI Strategy and Digital Automation
Las Vegas, NV · On-site
$99K - $137K/yr
Proficiency with vector databases (Vertex AI Vector Search, Pinecone) and agent orchestration frameworks (LangGraph, Google ADK). Minimum Qualifications: * Experience designing Context Graphs or ...
Pinecone Vector Databases information
What is a Pinecone Vector Database?
A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.
What are the key skills and qualifications needed to thrive as a Pinecone Vector Database Engineer, and why are they important?
To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.
What are some common challenges faced by engineers working with Pinecone Vector Databases, and how can they be addressed?
Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.
What is the difference between Pinecone Vector Databases vs Data Engineers?
| Aspect | Pinecone Vector Databases | Data Engineers |
|---|---|---|
| Primary Role | Managing and deploying vector database solutions for AI/ML applications | Designing, building, and maintaining data pipelines and infrastructure |
| Skills & Certifications | Knowledge of vector databases, cloud platforms, programming (Python, SQL) | Data modeling, ETL processes, cloud services, programming (Python, Java) |
| Work Environment | Tech companies, AI startups, cloud providers | Data-driven organizations, tech firms, finance, healthcare |
While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.
What are popular job titles related to Pinecone Vector Databases jobs in Nevada? For Pinecone Vector Databases jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Nevada look for? The top searched job categories for Pinecone Vector Databases jobs in Nevada are:
What cities in Nevada are hiring for Pinecone Vector Databases jobs? Cities in Nevada with the most Pinecone Vector Databases job openings:
Job description
AI Engineer
Las Vegas , NV
Onsite
Skills:-
Key Responsibilities
Las Vegas , NV
Onsite
Skills:-
Key Responsibilities
- Design and develop AI-powered applications using Python.
- Build Generative AI and LLM-based solutions using OpenAI, Azure OpenAI, Anthropic, or similar models.
- Develop RAG (Retrieval-Augmented Generation) applications using vector databases.
- Build REST APIs and integrate AI services with enterprise applications.
- Design AI agents, chatbots, and intelligent automation workflows.
- Develop data pipelines for AI/ML applications.
- Fine-tune, evaluate, and optimize AI models for performance.
- Deploy AI applications on AWS, Azure, or GCP.
- Collaborate with product, data engineering, and DevOps teams.
Required Skills
- 3–8 years of software development experience
- Strong Python programming
- Generative AI / Large Language Models (LLMs)
- OpenAI, Azure OpenAI, Anthropic, Gemini, or similar AI platforms
- LangChain or LlamaIndex
- RAG (Retrieval-Augmented Generation)
- Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, or Milvus)
- Prompt Engineering
- REST APIs
- Git & CI/CD
- SQL / NoSQL databases
- Docker
- Cloud Platform (AWS/Azure/GCP)
About Rapid Eagle
Sourced by ZipRecruiter
Rapid Eagle is dedicated to delivering testing solutions that help organizations take on important initiatives and reach their goals. They have a strong understanding of various industries and functions, utilize advanced technology, and operate on a global scale. The company encourages a culture of entrepreneurial thinking at all levels, promoting ownership, leadership, and accountability. What sets Rapid Eagle apart is their expertise in providing comprehensive testing solutions. They have a specialized team with extensive knowledge and experience, combining traditional values, a strong work ethic, and expertise in specific domains. The management team also has a deep understanding of client expectations. In short, Rapid Eagle Technologies is an IT company that focuses on testing solutions, brings together a skilled team with industry expertise, and strives to meet client expectations.
Industry
It services
Company size
11 - 50 Employees
Headquarters location
Fremont, CA, US
Year founded
2005