Agentic DevEx Engineer

Description

We are looking for an innovative Agentic DevEx Engineer to join our dynamic team in New York, New York. In this role, you will design and implement cutting-edge solutions that optimize engineering workflows and enhance artificial intelligence (AI) capabilities. Your expertise will drive the adoption of efficient development practices and ensure seamless collaboration between human engineers and AI agents.

Responsibilities:
Establish and enforce clear architectural boundaries within the codebase, ensuring proper domain separation and eliminating redundant modules.
Develop reproducible development environments with standardized commands for testing, linting, building, and other processes.
Document and maintain the organization of the codebase using structured files that serve as the single source of truth.
Design concise and high-signal guides to enhance agent accuracy and streamline their operational workflows.
Build reusable libraries of agent skills that include well-defined, domain-specific functions with clear operational contracts.
Implement deterministic workflows to allow agents to plan, read context, execute changes, and validate outputs effectively.
Codify and enforce engineering standards through linters and automated checks to ensure consistency across the codebase.
Improve validation infrastructure by establishing reliable test systems, reducing flakiness, and ensuring fast, accurate feedback from CI pipelines.
Create and maintain documented workflows for common engineering tasks, enabling efficient collaboration between engineers and AI tools.
Provide training and demonstrations to promote the adoption of AI collaboration patterns and ensure ease of use for the team.

Requirements

At least 3 years of experience in software development, with a focus on AI and machine learning.
Proficient in TensorFlow, React.js, Node.js, and Google Cloud Platform.
Strong understanding of artificial intelligence principles and experience with tools like Claude and automated agent generation.
Demonstrated ability to implement machine-readable context and ensure predictable navigation within complex codebases.
Expertise in creating and maintaining observability frameworks for large language models (LLMs) to ensure safety and monitoring.
Proven experience in driving adoption of new development tools and workflows within engineering teams.
Familiarity with designing automated review layers using CI checks, static analysis, and AI-powered tools.
Passionate about exploring and experimenting with the latest advancements in AI-assisted development technologies.

Technology Doesn't Change the World, People Do.

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