Senior/staff Software Engineer, Experience

Pinecone Pinecone · Data AI · New York, NY · R&D

This role focuses on building the infrastructure and interfaces for AI agents to interact with Pinecone's platform, including APIs, SDKs, and web surfaces. The goal is to make Pinecone the easiest and most capable platform for agentic workflows, emphasizing AI-assisted development and high-leverage systems.

What you'd actually do

  1. Pioneer our agent experience. Shape how AI agents interact with Pinecone — designing interfaces, protocols (MCP), and tooling that make Pinecone the easiest and most capable platform for agentic workflows to build on.
  2. Ship end-to-end experiences across API, SDK, CLI, and web. You'll own the full surface, from the HTTP layer to the UI, and you'll make calls across all of it.
  3. Build systems that multiply team output. We care about what ships, not how many hours went into it. Design AI-powered workflows, automated quality gates, and high-leverage platform capabilities that let a small team move at a pace that would otherwise require 10x the headcount.
  4. Set the standard for AI-assisted development on the team. Use the best tools available — Claude Code, Cursor, or whatever works — and help establish patterns that make the whole team faster.
  5. Collaborate with product, design, and engineering to identify what users (and agents) actually need and build it at the right abstraction level, at the right time.
  6. Build observable, auditable systems with monitoring, alerting, and verification mechanisms — because in a high-velocity environment, you need systems that tell you when something's wrong.

Skills

Required

  • At least 4 years of software engineering experience
  • A bias toward automation and leverage — you reach for systems and tooling before you reach for elbow grease
  • Hands-on experience shipping with AI coding tools (Claude Code, Cursor, Copilot, or similar) as a genuine part of your workflow
  • Proven ability to design and deliver versioned APIs, SDKs, or client libraries
  • Proficiency building web interfaces with React or similar
  • Experience with at least one major cloud provider (AWS, GCP, Azure)
  • Strong intuition for what makes APIs easy for both humans and agents to use correctly

Nice to have

  • Experience building or consuming MCP servers, or designing APIs explicitly for agent use cases
  • Familiarity with agentic frameworks and the emerging patterns around tool use, orchestration, and agent-to-agent communication
  • Strong familiarity with a compiled language like Rust, Go, or Java
  • Experience with large-scale open-source projects
  • Experience developing database or query engine SDKs

What the JD emphasized

  • agentic workflows
  • AI-assisted development
  • agent experience
  • AI agents

Other signals

  • AI agents as first-class users
  • agentic workflows
  • AI-native interfaces
  • AI-assisted development