AI Platform Engineer — Agentic AI & Developer Tools

Schonfeld

New York (NY)

On-site

USD 175,000 - 225,000

Full time

14 days+
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Job summary

Schonfeld is hiring multiple AI Engineers for the AI Platforms & Ops team to build and run the shared foundation powering AI applications firm-wide. You’ll contribute as an AI software engineer and strategist in a fast-paced environment where product requirements evolve with business stakeholder input.

The role covers end-to-end platform components, from agent framework to plugins, while emphasizing reliability, observability, and scalable deployment.

Qualifications

  • Experience developing agentic AI applications, harnesses, MCP servers and workflows.
  • Familiarity with AI agents, RAG pipelines and agentic tools is preferred.
  • Experience building developer-facing platforms or internal tooling used by engineering teams.
  • Exposure to identity, entitlements and software supply chain management.

Responsibilities

  • Own a component of the AI platform end-to-end, evaluating options and deploying at scale.
  • Build and operate across the platform surface: agent framework, tooling, and plugin marketplace.
  • Develop observability tooling to make agents testable and safe to release.
  • Collaborate with AI Solutions to turn patterns into reusable platform components.
  • Raise code quality and improve development lifecycles and platform reliability.

Skills

Agentic AI apps
MCP servers
Workflows
AI agents
RAG pipelines
DataDog observability
Developer platforms
Identity & entitlements
Software supply chain

Tools

DataDog

Job description

Schonfeld is hiring multiple AI Engineers for the AI Platforms & Ops team to build and run the shared foundation powering AI applications firm-wide. You’ll contribute as an AI software engineer and strategist in a fast-paced environment where product requirements evolve with business stakeholder input.

The role covers end-to-end platform components, from agent framework to plugins, while emphasizing reliability, observability, and scalable deployment.

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