Software Engineer – Developer Experience & AI Platform

ID.me•McLean, VA

15h•Onsite

About The Position

ID.me is seeking a Software Engineer (SDE3) for its Developer Experience and AI Platform team within Core Platform Engineering. The role builds tools, systems, and platforms that reduce operational friction and cognitive load across engineering, helping teams build and ship software efficiently while protecting production. The team develops an API-first platform and uses AI and agentic systems to improve developer workflows. The engineer will design and evolve programming-language-specific paved paths that standardize service creation, CI/CD, observability, and security. The role also builds and integrates AI agents and agentic workflows—including MCP integrations, RAG-powered developer context, and automated remediation—to automate service ownership, upgrades, and maintenance across the codebase. This position is based in McLean, Virginia, and requires full-time in-office attendance. The role involves driving platform initiatives from technical design through rollout, adoption, and operational support; measuring outcomes using DORA metrics and developer satisfaction; and enabling other engineers through documentation, code reviews, pairing, and workshops.

Requirements

Bachelor’s or graduate degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
At least 3 years of professional software development experience building backend services, developer tooling, or platform automation.
Strong proficiency in at least one modern programming language, such as Go, Python, Ruby, TypeScript/JavaScript, or Java, and ability to work across multiple language ecosystems.
Demonstrated experience using and building with modern AI and agentic AI tools, such as Claude Code, Cursor, LLM APIs, MCP servers, or agentic frameworks.
Strong interest in automation, self-service system design, and reducing cognitive load for engineers.

Nice To Haves

Experience on a Developer Experience, Internal Developer Platform, AI Enablement, or Platform Engineering team.
Hands-on experience designing or building autonomous AI agents, custom MCP tools or servers, RAG systems, or LLM-powered CI/CD and code-maintenance workflows.
Experience building language-specific scaffolding, SDKs, linters, codemods, or standardized build and deployment templates across multiple languages.
Familiarity with modern CI/CD platforms, especially reusable GitHub Actions workflows; Docker; Kubernetes; and Internal Developer Portals such as Backstage.
Experience with GCP or AWS and Infrastructure as Code such as Terraform.
Understanding of production observability, including metrics, logs, and traces, and embedding security or compliance guardrails such as FedRAMP, SOC 2, or NIST in developer pipelines.
Systems-level thinking and strong written and verbal communication skills, with the ability to champion standards through enablement and intuitive tooling.
Ownership of a significant platform tool, automation pipeline, or AI-enabled workflow from design through organization-wide adoption.

Responsibilities

Design, build, and maintain internal developer tools, CLI utilities, Internal Developer Portal workflows, and reusable GitHub Actions, incorporating automated guardrails for breaking changes, security gaps, and compliance regressions.
Create and maintain language-specific paved paths, including project scaffolding, SDKs, shared libraries, container base images, and standardized CI/CD templates that include production-readiness, observability, and security best practices.
Build and operate AI-native developer platform capabilities, including MCP servers and registries, context-engineering and RAG pipelines, and AI coding assistant integrations.
Design and deploy autonomous and human-in-the-loop AI agents to automate recurring engineering ownership and maintenance tasks such as upgrades, vulnerability remediation, configuration migrations, test generation, and standards enforcement.
Partner with product, infrastructure, SRE, and security teams to identify development lifecycle bottlenecks and replace manual processes or ticket queues with self-service automation.
Drive medium-to-large platform initiatives from technical design through rollout, adoption, and operational support; measure impact using DORA metrics and developer satisfaction.
Promote AI-augmented engineering workflows, write documentation, and mentor engineers through code reviews, pairing, and enablement workshops.