The Role

This is a high-accountability environment where bold ideas drive real innovation for customers, partners, and the industry. . The successful candidate will take ownership, deliver meaningful impact, and help shape the future of AI-ready connectivity.

Lumen is seeking an experienced and hands-on Senior Lead Software Developer, AI Developer Enablement to help shape the next chapter of AI-assisted software engineering across the organization. This role will define, build, and scale reusable AI capabilities that accelerate developer productivity, reduce friction in everyday engineering work, and transform practical AI workflows into high-impact accelerators for teams across the enterprise.

The ideal candidate will bring deep expertise in modern software development, AI-assisted engineering workflows, developer tooling, automation, APIs, cloud platforms, and enterprise engineering practices. This individual will work closely with engineering, platform, DevSecOps, security, product, and AI teams to translate developer pain points into secure, scalable tools, skills, agents, and patterns that teams are eager to adopt.

As the Senior Lead Software Developer, AI Developer Enablement, the candidate will play a visible role in helping engineers write, test, review, troubleshoot, document, and deliver software with greater speed and confidence. This is a builder role for an individual who enjoys progressing from bold ideas and working prototypes to production-ready enablement capabilities that make AI useful in the daily flow of software delivery.

The ideal candidate should possess a strong understanding of generative AI principles, agentic AI workflows, prompt design, code generation, knowledge retrieval, software delivery practices, responsible AI, and secure enterprise adoption patterns. This role will help make AI enablement practical, measurable, and transformational for developers across Lumen.

Location

This is a work from home position within the US.

The Main Responsibilities

AI-Assisted Development Enablement

• Design and implement AI-enabled developer workflows for code generation, reviews, debugging, testing, documentation, research, incident triage, and platform navigation. Establish scalable, secure, and repeatable patterns for AI adoption across engineering teams.
• Develop reusable prompts, agents, integrations, and workflow accelerators that improve developer productivity while aligning with architecture, security, governance, and operational standards.

Developer Productivity & Experience

• Identify development friction and translate it into high-impact AI solutions. Partner with engineering teams to reduce toil, accelerate delivery, improve onboarding, and enhance the developer experience from ideation through production.
• Define adoption metrics, feedback loops, and success measures to demonstrate improvements in quality, delivery speed, developer confidence, and overall performance.

Reusable AI Capabilities & Patterns

• Build and scale shared AI capabilities, reference architectures, prompt libraries, templates, and playbooks that teams can adopt quickly and consistently.
• Partner with platform, architecture, and security teams to ensure AI solutions are maintainable, discoverable, observable, governed, and aligned with responsible AI practices.

Technical Knowledge & AI-Driven Support

• Improve access to engineering knowledge through AI-powered search, summarization, technical Q&A, documentation generation, and context-aware support.
• Transform tribal knowledge, coding standards, platform guidance, and operational playbooks into scalable AI-assisted experiences.

AI Adoption & Community Enablement

• Drive AI adoption through demos, training, office hours, onboarding resources, reusable examples, and engineering community engagement.
• Coach developers and technical leaders on practical AI usage, safe experimentation, measurable outcomes, and responsible engineering practices.

Technical Delivery & Project Execution

• Lead AI enablement initiatives from discovery through production. Define plans, milestones, dependencies, user validation, and production readiness.
• Identify and mitigate risks related to security, data access, hallucinations, quality, compliance, integrations, user experience, and operational support.

Measurement & Continuous Improvement

• Measure AI impact through adoption, usage, cycle time reduction, automation, developer satisfaction, and quality improvements.
• Use data and feedback to refine AI enablement strategies, retire low-value initiatives, and scale high-impact capabilities.

Leadership & Technical Influence

• Provide technical leadership and mentorship for AI developer enablement. Foster innovation, accountability, collaboration, experimentation, and continuous improvement.
• Guide teams on architecture, prompt engineering, agent workflows, integration patterns, responsible AI, and safe implementation of AI-powered developer solutions.

What We Look For in a Candidate

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Advanced degree or equivalent practical experience preferred.
• 10 years of experience in software development, platform engineering, developer productivity, AI enablement, automation, or related technical disciplines.
• Strong 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.
• Deep understanding of the software development lifecycle, code quality, testing, documentation, secure coding, CI/CD, operational reliability, and production support practices.
• Proven ability to translate ambiguous developer needs into practical, secure, scalable, and reusable technical solutions.
• Experience partnering with cross-functional teams including engineering, platform, security, product, architecture, operations, and business stakeholders
• Strong communication skills with the ability to explain technical concepts, demonstrate AI-enabled workflows, influence adoption, and create clear enablement materials.
• Strong understanding of responsible AI, data protection, security considerations, governance, and risk management for enterprise AI adoption.
• Demonstrated ability to mentor engineers, lead technical initiatives, and drive measurable improvements in developer productivity and engineering outcomes.

Preferred Skills

• Experience with LLM-based developer tools, AI coding assistants, agent frameworks, retrieval-augmented generation, vector search, tool calling, or workflow orchestration.

Requisition #: 342834