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# Software Engineer - Developer Experience & AI Platform

- **Company:** APi Inc
- **Location:** McLean, VA, United States
- **Experience:** Experienced
- **Salary:** $120,000.0 - $159,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Automation of Tests, Code Review, Computer Programming, Continuous Integration, Cursor, Programming Tools, Github, Python (Programming Language), Reliability Engineering, Ruby, Software Engineering, TypeScript, Software Vulnerability Management, Retrieval-Augmented Generation, Large Language Models, Claude Code, Backend, Agentic-AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Model Context Protocol, Terraform, Network Server, Docker, Golang, Programming Languages
- **Published:** October 27, 2026
- **Apply:** https://startup.jobs/software-engineer-developer-experience-ai-platform-idme-10583653

## About the Role

* Bachelor's or Graduate degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience).
 * 3+ years of professional software development experience building backend services, developer tooling, or platform automation.
 * Strong proficiency in at least one modern programming language (e.g., Go, Python, Ruby, TypeScript/JavaScript, or Java) and ability to work across multiple language ecosystems to build language-specific tooling and paved paths.
 * Demonstrated track record of using and building with modern AI and Agentic AI tools (e.g., Claude Code, Cursor, LLM APIs, MCP servers, or agentic frameworks) to accelerate software delivery and automate engineering workflows.
 * Deep passion for automation, self-service system design, and reducing cognitive load for other engineers., * Experience working on a Developer Experience (DevEx), Internal Developer Platform (IDP), AI Enablement, or Platform Engineering team.
 * Hands-on experience designing or building autonomous AI agents, custom MCP tools/servers, RAG systems, or LLM-powered CI/CD and code-maintenance workflows.
 * Experience building programming-language-specific scaffolding, SDKs, linters, codemods, or standardized build/deployment templates across multiple languages.
 * Strong familiarity with modern CI/CD platforms (especially GitHub Actions reusable workflows), containerization (Docker, Kubernetes), and Internal Developer Portals (e.g., Backstage).
 * Experience with cloud platforms (GCP or AWS) and Infrastructure as Code (e.g., Terraform).
 * Understanding of production observability (metrics, logs, traces) and embedding security/compliance guardrails (e.g., FedRAMP, SOC2, NIST) directly into developer pipelines.
 * Systems-level thinking with strong written and verbal communication skills-able to champion standards through enablement and intuitive tooling rather than manual mandates.
 * Demonstrated ownership of at least one significant platform tool, automation pipeline, or AI-enabled workflow from design through organization-wide adoption.

## Description

* Build Self-Service Platforms & Intelligent Guardrails: Design, build, and maintain internal developer tools, CLI utilities, Internal Developer Portal (IDP) workflows, and reusable GitHub Actions that make building and deploying services fast and intuitive-while embedding automated guardrails that make it hard for engineers to introduce breaking changes, security gaps, or compliance regressions.
 * Develop & Evolve Language-Specific Paved Paths: Create and maintain opinionated, programming-language-specific "golden paths" (including project scaffolding, SDKs, shared libraries, container base images, and standardized CI/CD templates) that bake in production readiness, observability, and security best practices by default.
 * Superpower Developer Workflows with AI & Agentic Systems: Build and operate AI-native developer platform capabilities-including Model Context Protocol (MCP) servers/registries, context-engineering and RAG pipelines, and AI coding assistant integrations-that optimize both human developer cognitive load and AI context windows.
 * Automate Ownership & Maintenance with Autonomous AI Agents: Design and deploy autonomous and human-in-the-loop AI agents that automate recurring engineering ownership and maintenance toil-such as dependency and framework upgrades, vulnerability remediation, configuration migrations, automated test generation, and standards enforcement.
 * Eliminate Toil & Manual Ticket Queues: Partner with product, infrastructure, SRE, and security teams to identify high-friction bottlenecks in the software development lifecycle and replace manual processes or ticket queues with 100% self-service automation.
 * Own End-to-End Platform Features: Drive medium-to-large Developer Experience and AI Platform initiatives from technical design through rollout, adoption, and operational support, measuring impact via DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore) and developer satisfaction.
 * Champion Enablement & Mentorship: Evangelize modern AI-augmented engineering workflows, write clear documentation, and mentor fellow engineers through code reviews, pairing, and enablement workshops.