Remote Senior Lead AI Developer Enablement

United States Digital Space LLC

United States

Remote

USD 150,000 - 210,000

Full time

14 days+

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Job summary

United States Digital Space LLC is seeking a Senior Lead Software Developer, AI Developer Enablement to shape AI-assisted software engineering across the enterprise. You will define, build, and scale reusable AI capabilities that accelerate developer productivity, reduce friction, and transform AI workflows into high-impact accelerators for teams.

The ideal candidate will bring deep expertise in modern software development, AI-assisted engineering workflows, developer tooling, automation, APIs,

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
10+ years of experience in software development, platform engineering, developer productivity, AI enablement, automation, or related technical disciplines.
Hands-on experience designing, building, and supporting modern software solutions, developer tools, APIs, integrations, automation frameworks, or internal platforms.
Experience with AI-assisted development workflows, coding assistants, generative AI capabilities, prompt engineering, agentic workflows, or applied AI solutions for engineering teams.
Strong understanding of software development lifecycle, code quality, testing, documentation, secure coding, CI/CD, operational reliability, and production support practices.

Responsibilities

Design AI-enabled developer workflows for code generation, reviews, debugging, testing, documentation, research, incident triage, and platform navigation.
Develop reusable prompts, agents, integrations, and workflow accelerators to improve developer productivity while aligning with security and governance standards.
Identify development friction and translate into high-impact AI solutions; collaborate with engineering teams to reduce toil and accelerate delivery.
Define adoption metrics, feedback loops, and success measures to demonstrate improvements in quality and delivery speed.
Build and scale shared AI capabilities, reference architectures, prompt libraries, templates, and playbooks for rapid adoption.
Improve access to engineering knowledge through AI-powered search, summarization, Q&A, and documentation generation.