Lead Software Engineer (AI Developer Tooling & Enablement)

Lead Software Engineer (AI Developer Tooling & Enablement)

Beaverton, OR (Hybrid/Remote flexibility) but need local only

Contract

Video Interview

Two recent direct manager references

Public LinkedIn profiles required

AI developer tooling, GitHub administration, platform engineering, CI/CD pipelines, Python/Golang, Kubernetes, AI-assisted development tools (Copilot/Cursor/Claude), automation frameworks, SCIM/identity integrations, and enterprise developer experience platforms.

Job Summary

We are seeking a Lead Software Engineer specializing in AI Developer Tooling & Enablement to help design and build internal platforms, tools, and frameworks that accelerate AI/ML development across engineering teams. The ideal candidate will have strong experience building scalable developer platforms, enabling AI workflows, and supporting machine learning engineers through automation and tooling.

Key Responsibilities

Design and develop developer tooling, frameworks, and platforms that support AI/ML engineering teams.

Build scalable APIs, services, and automation pipelines to streamline model development, deployment, and monitoring.

Enable engineering teams by improving developer experience (DX) for AI development.

Collaborate with ML engineers, data scientists, and platform teams to deliver reusable tooling and infrastructure.

Develop and maintain CI/CD pipelines for AI model lifecycle management.

Ensure best practices for scalability, security, observability, and performance across AI development platforms.

Mentor engineers and lead technical initiatives across multiple teams. Required Qualifications

8+ years of software engineering experience with platform or developer tooling development.

Strong programming experience in Python, Java, or Go.

Experience building AI/ML developer platforms, internal tools, or ML infrastructure.

Hands-on experience with cloud platforms (AWS, GCP, or Azure).

Strong understanding of APIs, microservices architecture, and distributed systems.

Experience working with CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes). Preferred Qualifications

Experience with ML platforms such as MLflow, Kubeflow, or SageMaker.

Knowledge of LLMs, GenAI frameworks, or model development workflows.

Background supporting developer experience (DX) improvements and internal engineering tools.

Experience leading technical initiatives or mentoring engineers.