Applied AI Engineer (Full-Stack)

Pinecone is hiring an Applied AI Engineer (Full-Stack) for a remote role open to applicants in United States. It pays $190k-$270k a year and Level rates it ; you can apply on Pinecone.

Level's read on this job

Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts in line with the typical AI engineer posting on Level.
This is listed as a remote role.
The posting mentions RAG and LLM integration among its tools and skills.
Pinecone has 4 other open roles on Level.

AI in this role

ragllm-integration

About Pinecone

Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable.

About the Team and Role

We're looking for an Applied AI Engineer who loves building real applications with AI. You'll work across the stack, from backend services and retrieval pipelines to APIs and user-facing applications, turning new AI capabilities into working solutions.

This is a hands-on engineering role for someone who enjoys moving quickly, experimenting with emerging technologies, and owning projects from initial idea to production.

You'll work closely with our engineering and product teams, as well as customers and partners, to explore new use cases, build reference applications, and demonstrate what's possible with Pinecone's technology.

The ideal candidate combines strong full-stack engineering skills with practical experience building LLM-powered applications and agentic systems. You should be equally comfortable discussing architecture, writing production code, and putting together a working prototype.

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 that help developers and customers adopt Pinecone.
Experiment with emerging AI patterns, including RAG, agents, tool use, context engineering, and agent memory.
Work with customers, partners, and internal teams to understand real-world problems and translate them into working software.
Evaluate and improve the quality, reliability, latency, and cost of AI-powered applications.
Share technical insights and best practices through code, examples, and technical content.
Bring learnings from building applications back into Pinecone’s product and engineering teams.

What You’ll Bring to the Table

You don't need to check every box, but you should enjoy building software and be excited about what AI makes possible.

Full-Stack Engineering

Strong software engineering background with experience designing, building, and shipping production applications.
Proficiency in Python and/or TypeScript, including modern backend frameworks and frontend technologies such as React or Next.js.
Experience building APIs, integrating external services, and working with databases and cloud infrastructure.
Ability to independently take a project from rough requirements through implementation and deployment.

Applied AI

Hands-on experience building applications using LLMs, embeddings, vector databases, or retrieval-augmented generation.
Familiarity with modern AI development tools, frameworks, and APIs.
Understanding of the practical challenges of building AI applications, including retrieval quality, evaluation, latency, reliability, and cost.
Curiosity about emerging patterns in agentic applications, context management, and AI-driven workflows.

Ownership & Collaboration

A builder's mindset: you enjoy writing code, experimenting, and getting working software into users’ hands.
Comfortable working with ambiguous requirements and making pragmatic technical decisions.
Ability to communicate technical ideas clearly to engineers, customers, and other stakeholders.
Comfortable moving between rapid prototypes and production-quality implementations.
Interest in understanding how developers and customers use the technology and translating that feedback into better solutions.

Bonus Points

Experience with Pinecone or other vector databases and search technologies.
Experience building agentic applications, agent memory systems, or complex RAG pipelines.
Contributions to open-source projects, developer tools, or technical communities.
Experience working directly with customers on technical projects.
Experience deploying and operating AI applications in production.

Perks & Benefits

Comprehensive health coverage including medical, dental, vision, and mental health resources
401(k) Plan
Equity award
Flexible time off
Paid parental leave
Annual Company Retreat
WFH Equipment Stipend

Benefits and eligibility may vary by country of employment.

How we rate this

Applied AI Engineer (Full-Stack) at Pinecone rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied AI Engineer (Full-Stack) is an open job at Pinecone.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $190k-$270k a year.
The role is based in New York City and is marked remote.
The job was posted on October 22, 2026.
Applications are handled by Pinecone. Apply on Pinecone

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGLLM Integration

Also common in AI engineer jobs at this level

Machine learning AWS AI agents Generative AI Azure Google Cloud

Pay

This job starts at: $190k
Typical AI engineer job: $183k

This posting starts close to the typical AI engineer job. See AI engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How have you integrated a large language model into a production application?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG and LLM Integration. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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