Applied AI Engineer - Full-Stack LLM & RAG Apps

Pinecone; New York (NY); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Comprehensive health coverage

401(k) Plan

Equity award

Flexible time off

Paid parental leave

Annual Company Retreat

WFH Equipment Stipend

Job summary

Pinecone in New York is looking for an Applied AI Engineer who loves building real AI-powered applications. You’ll work across the stack—from backend services and retrieval pipelines to APIs and user interfaces—turning new AI capabilities into working software.

Ideal candidates have strong full-stack skills and practical experience with LLMs, embeddings, vector databases, and RAG patterns. You’ll collaborate with customers and teams to ship prototypes and production solutions.

Qualifications

• Strong software engineering background with production experience.
• Hands-on experience building LLM-powered apps and AI workflows.
• Ability to design and ship full-stack solutions end-to-end.

Responsibilities

• Design, build, and ship end-to-end AI applications using Pinecone's retrieval and knowledge infrastructure.
• Develop full-stack solutions spanning frontend interfaces, backend services, APIs, data pipelines, and LLM integration.
• Build reference applications, integrations, and reusable components for developers and customers.
• Experiment with emerging AI patterns, including RAG, agents, tool use, context engineering, and agent memory.
• Collaborate with customers, partners, and internal teams to translate problems into working software.
• Evaluate and improve reliability, latency, and cost of AI-powered applications.
• Share technical insights and best practices through code and content.
• Bring learnings back into Pinecone’s product and engineering teams.

Skills

Python

TypeScript

React/Next.js

APIs

Cloud infrastructure

LLMs/Embeddings

Vector databases

RAG patterns

Job description

Pinecone in New York is looking for an Applied AI Engineer who loves building real AI-powered applications. You’ll work across the stack—from backend services and retrieval pipelines to APIs and user interfaces—turning new AI capabilities into working software.

Ideal candidates have strong full-stack skills and practical experience with LLMs, embeddings, vector databases, and RAG patterns. You’ll collaborate with customers and teams to ship prototypes and production solutions.