Senior Software Engineer II- AI Developer Experience (Remote USA)

Optro

1d • $156,000 - $214,500 • Remote

About The Position

At Optro, we believe a "developer" is anyone who works with code—be that an engineer, a designer, a product manager, or an AI agent. Our mission is to build a platform where all of them can ship value seamlessly, safely, and without friction. The APEX (AI Practice and Experience) team is at the absolute forefront of this paradigm shift. We build the capabilities that turn raw AI investments into practical, high-leverage tools for our internal innovators. As a Senior Software Engineer II within APEX, you will partner with our Tech Lead to architect and evolve this ecosystem. Your primary canvas is SATL (Shared AI Tooling Layer)—our internal platform providing the hooks, skills, and contextual infrastructure that allow both human engineers and automated tools to work cohesively. Because the AI space is changing daily, this role offers a unique dual mandate: you will build production-grade platforms while acting as our lead technical scout. You will stay at the absolute cutting edge of industry research—evaluating emerging frameworks, testing new protocols, and separating real architectural progress from passing hype to ensure we focus our energy on what truly multiplies developer velocity. You will collaborate closely with your colleagues on the DX (Developer Experience) team. While they maintain the fast repository loop, codebase standards, and repository health required to write, run, and ship quality code efficiently, you will build the intelligent context, guardrails, and integrations that allow automated assistants to understand what to build and how to build it safely.

Requirements

• 6+ years of professional software engineering experience, with a solid history of building internal developer platforms, developer tools, or shared API infrastructure.
• AI Tooling Extension: Hands-on experience building with or extending developer-facing AI tools (such as designing custom CLI helpers, building developer integrations, or creating Model Context Protocol (MCP) servers).
• Practical LLM Integration: Substantial hands-on experience working with LLM APIs, building system prompts, and orchestrating stateful programmatic workflows.
• Technical Mastery: Deep proficiency in TypeScript and Node.js, combined with expert-level comfort writing shell scripting and building CLI tooling.
• Evaluative Rigor & Signal Filtering: Proven expertise in critically evaluating emerging technical architectures, bypassing marketing hype, and making pragmatic, evidence-based recommendations on tooling adoption.
• Platform Mindset: Strong architectural instinct for designing clean, extensible abstractions and APIs that other developers (and automated scripts) can reliably consume.
• Communication & Influence: A collaborative track record of driving technical alignment and platform adoption across a 300+ person organization through empathy, clear evidence, and EDD (Engineering Design Doc)-driven alignment.
• Comfort with Ambiguity: Adaptive and proactive in the face of rapidly evolving developer tooling, with a history of adapting and leading through technical uncertainty.

Nice To Haves

• Deep experience customization or workflow development specifically using Claude Code (primarily) or GitHub Copilot (secondarily).
• Experience building or maintaining shared tooling layers, internal CLI frameworks, or developer telemetry pipelines.
• Familiarity with monorepo architectures and how automated tooling interacts with build tools (e.g., pnpm, Turborepo).

Responsibilities

• Develop within SATL: Architect and build core workflows, hooks, and services within the Shared AI Tooling Layer (SATL) to integrate off-the-shelf LLMs deeply into our engineering environment.
• Lead Technical Scouting & Prototyping: Continuously research, prototype, and evaluate rapid advancements in the AI developer-tooling space (e.g., new LLM APIs, agentic orchestration, context-management protocols, and IDE integrations). Strategically define which technologies are ready for platform-level adoption and which are distractions to be safely ignored.
• Expand the SATL Platform: Design, scale, and maintain the shared foundation of SATL for distributing and managing AI tool configurations, establishing a highly reliable, performant framework for shared rules, skills, lifecycle hooks, and MCP configurations across developer environments.
• Build Safe Execution Environments: Create the runtime guardrails, permission scoping, and execution sandbox patterns required for safe, programmatic codebase modifications.
• Architect Platform Observability: Build telemetry systems that track automated tooling interactions, token consumption, and execution paths, providing visibility into programmatic contributions.
• Track Tooling Utility: Establish the infrastructure to measure the quality and impact of automated contributions (e.g., analyzing automated PR success rates) to shape our platform roadmap.
• Strategic Partnership: Collaborate closely with platform, security, and developer infrastructure stakeholders to align automation guardrails, security baselines, and developer-facing APIs across PED.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed