Security Engineer II, Security Platform

Remitly•Seattle, WA

6d•Hybrid

About The Position

Remitly is seeking an AI-forward Security Engineer to join Security Platforms, part of Security & Privacy. The team builds shared systems used by security teams, with the objective of establishing clear ownership for every asset and identity, automating routine security work as audited services, and building guardrails for AI tools into company tooling. In this role, you will design, build, and operate production services that make secure practices the default for Remitly’s engineers, employees, and AI agents. Working alongside a Staff Security Engineer, you will help turn internal security tools into supported services used across the company. Success calls for strength in software engineering, cloud security, and agentic development, as well as curiosity and a willingness to learn new tools.

Requirements

Experience building, operating, and supporting production services through software engineering.
Proficiency in a programming language such as Python or Golang.
Experience building security automation or risk detection tooling.
Hands-on experience delivering production or open-source software through agentic development.
Experience designing data models and APIs used by other teams.
Experience building on cloud-native infrastructure such as AWS, GCP, and Kubernetes.
Working knowledge of at least one security area, such as cloud and infrastructure, identity and access, or application security, and the industry frameworks applicable to it.
Clear communication with engineers and partners, and experience influencing other teams without formal authority.
Curiosity demonstrated by experimenting, building, and staying current on open-source and new security tools.

Nice To Haves

Experience with agent frameworks such as LangChain, LangGraph, and CrewAI, or experience building tools and MCP servers for AI agents.

Responsibilities

Build services and data pipelines that create an inventory and ownership graph for devices, cloud assets, SaaS applications, AI systems, and non-human identities, routing findings to the appropriate teams.
Build agents and workflows to automate security and privacy design reviews and vulnerability triage.
Deliver managed settings, hooks, and approval paths for AI agents, connectors, and Model Context Protocol (MCP) servers.
Move security scripts and scheduled jobs to an audited automation platform with human approval steps; provide production-service testing, monitoring, and on-call coverage.
Partner with infrastructure, IT, and product engineering teams to integrate the platform into their workflows and use their feedback to guide development.
Provide thorough code reviews, participate in design reviews, maintain runbooks, and help engineers across Security & Privacy build with agents and code.