Lead Developer Relations Engineer

Zeta Global

20h•$170,000 - $200,000

About The Position

We are seeking a hands-on, technical Lead Developer Relations Engineer to drive adoption of AI-native software engineering workflows, tooling, and best practices across the software development lifecycle. This role sits at the intersection of engineering, AI enablement, developer productivity, and technical evangelism, helping teams successfully adopt and scale modern AI-assisted development patterns. You will own the Developer Relations charter for AI-native engineering, shaping how developers leverage coding assistants, autonomous agents, AI-assisted testing, spec-driven development, and agentic workflows in real-world engineering environments. This includes technical content, demos, workflow examples, workshops, onboarding assets, social engagement, and enablement programs that accelerate AI adoption across engineering teams and the broader developer ecosystem. This role requires a strong builder mindset with the ability to combine deep technical expertise, developer empathy, technical storytelling, and community engagement. You should be equally comfortable writing code, building demos, experimenting with AI-native tooling, creating educational content, engaging with developers online, and helping teams operationalize modern AI-assisted engineering workflows at scale.

Requirements

Proven experience in Developer Relations, Developer Experience, Platform Engineering, AI Enablement, Solutions Engineering, or related technical roles.
Strong software engineering background with proficiency in TypeScript, Python, and modern software development workflows.
Hands-on experience using AI-native engineering tools such as Cursor, Claude Code, Codex, Github Copilot, MCP servers, or autonomous developer agents in real-world engineering environments.
Deep understanding of modern AI-assisted software development practices including agentic workflows, prompt-driven development, AI-assisted testing, automated code review, and developer productivity optimization.
Strong technical storytelling, communication, and developer education skills with experience creating blogs, demos, tutorials, workshops, videos, social content, or technical enablement material.
Experience engaging developer communities through technical discussions, online platforms, workshops, webinars, hackathons, or open-source ecosystems.
Strong cross-functional collaboration, communication, and problem-solving skills with a hands-on builder mindset.

Nice To Haves

Experience building developer communities, technical audiences, newsletters, or AI engineering content channels.
Experience with AI-assisted SDLC tooling, evaluation systems, verification frameworks, or autonomous software engineering workflows.
Familiarity with cloud-native systems, Kubernetes, CI/CD, observability, and developer infrastructure platforms.
Contributions to open-source developer tooling, AI engineering ecosystems, or technical education initiatives.
Familiarity with developer productivity frameworks such as DORA or SPACE.

Responsibilities

Drive adoption of AI-native engineering workflows including coding assistants, autonomous agents, MCP ecosystems, AI-assisted testing, code review, and spec-driven development practices.
Create high-impact technical content including blogs, tutorials, architecture guides, demos, workshops, videos, implementation playbooks, and workflow education material focused on AI-native software engineering and developer productivity.
Build demo repositories, reusable workflow examples, and practical implementation patterns that help engineering teams adopt AI-native development practices using tools such as Cursor, GitHub Copilot, Anthropic, OpenAI Codex, MCP servers, and autonomous developer agents.
Drive developer engagement and ecosystem awareness through technical storytelling, developer education initiatives, online engagement, social platforms, workshops, webinars, hackathons, and community participation.
Partner with Engineering, Platform, AI Enablement, and Developer Experience teams to improve adoption of AI-native workflows, developer tooling, and agentic development practices across the organization.
Educate developers on emerging AI-native engineering paradigms including prompt-driven development, agent orchestration, AI-assisted testing, verification-first workflows, and autonomous software delivery patterns.
Act as an advocate for developer productivity and workflow transformation by identifying friction points and enabling scalable AI-assisted engineering practices.
Measure and improve adoption of AI-native engineering practices through developer feedback, workflow telemetry, productivity metrics, content engagement, onboarding insights, and enablement outcomes.