Principal Software Engineer, AI Developer Tools

10+ years software engineering experience 3+ years in Staff or Principal Engineer roles Deep expertise in AI/ML technologies with hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools Strong understanding of LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, agent orchestration frameworks, and practical applications of AI in software development workflows Proven track record of architecting and building highly scalable distributed systems and developer-facing platforms Production experience with modern cloud-native infrastructure including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines Proficiency in Go (preferred), Rust, Java, or Python Strong software engineering fundamentals Experience designing developer tools, platform engineering systems, or internal tools that enable other teams Exceptional product and platform mindset Strong communication skills with ability to influence technical and non-technical stakeholders Track record of technical mentorship and elevating engineering teams' capabilities Ownership mentality with bias for action and iterative delivery in ambiguous, fast-moving environments Comfortable with autonomous work in distributed, remote-first teams across multiple time zones Experience with MCP (Model Context Protocol) or similar AI agent integration standards (preferred) Background in developer productivity, DevOps, SRE, or platform engineering domains (preferred) Contributions to open source AI tools, developer tooling, or platform engineering projects (preferred) Experience productizing internal platforms or tools into commercial offerings (preferred) Deep knowledge of security, compliance, and operational best practices for production AI systems (preferred) Experience with infrastructure-as-code frameworks (Terraform, Pulumi) and multi-cloud platforms (AWS, GCP, Azure) (preferred)

Define the long-term technical vision and architecture for AI-powered developer tools and the self-service platform Establish architectural patterns, technical standards, and best practices for LLM integration, AI agent development, and production AI systems Lead technical strategy for platform capabilities including deployment frameworks, observability integration, security controls, and operational tooling Design highly available, scalable infrastructure for hosting AI agents and developer tools Drive technical decisions on AI technology choices, LLM provider strategies, prompt engineering approaches, and agent orchestration frameworks Partner with Senior Manager and product leadership to align technical architecture with business objectives and productization opportunities Architect and build production-ready AI agents for developer productivity Design and implement the self-service platform infrastructure Build systems that accelerate adoption of AI-native development tools across Docker's engineering organization Establish reliability, security, and performance standards for AI systems Design integration points between AI developer tools and existing developer infrastructure Lead technical implementation of AI tools that improve early-stage development metrics Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks Define technical approach for productizing internal AI developer tools into customer-facing offerings Drive technical standards for measuring AI tool effectiveness Optimize AI tool performance, cost efficiency, and developer experience Lead cross-functional technical discussions influencing company-wide AI and developer tooling architecture Mentor senior and staff engineers on AI/LLM integration patterns, agent development, and platform engineering best practices Lead design reviews and technical decision-making for production AI systems Foster culture of technical excellence, experimentation, and rapid prototyping Serve as primary technical contact and thought leader for AI in developer workflows Collaborate with platform teams to establish shared technical standards and integration patterns