Lead Software Engineer, AI

Lead Software Engineer, AI Experience

Penn Foster Group Fully remote within the United States

Position Summary

As a Lead Software Engineer, AI Experience at Penn Foster Group, you will provide technical leadership for the design and delivery of AI-native products that help millions of learners discover, enroll in, and progress through our programs.

You will operate across product, engineering, and platform boundaries—turning ambiguous opportunities into reliable, scalable systems and establishing the technical direction for AI experiences across the organization. This is a hands-on role requiring strong full-stack execution, architectural judgment, and the ability to influence through technical strategy, design, and mentorship.

You will help define how Penn Foster builds with AI by developing retrieval pipelines, agentic workflows, evaluation systems, and production-grade model integrations. You will partner with engineering leaders and product teams to identify high-leverage opportunities, shape technical roadmaps, raise engineering standards, and guide initiatives from early exploration through production adoption.

Essential Job Functions

• Define technical strategy and architecture for AI-powered product experiences across the learner and content-authoring ecosystem.
• Design, build, and ship full-stack systems using TypeScript, Vue.js, Node.js, PostgreSQL, and Azure.
• Lead complex, cross-functional initiatives from problem definition through delivery, adoption, and ongoing improvement.
• Establish reusable patterns for retrieval-augmented generation, agentic workflows, model orchestration, prompt management, and human-in-the-loop experiences.
• Design and maintain evaluation frameworks, quality metrics, observability, and feedback loops for LLM-powered features.
• Integrate model APIs from Anthropic, OpenAI, and other providers with careful attention to reliability, latency, token usage, cost, privacy, security, prompt-injection risk, and graceful degradation.
• Own technical direction for AI-powered content authoring and management capabilities.
• Partner with product, platform, design, data, and sibling engineering teams to translate ambiguous problems into coherent technical plans and shippable systems.
• Identify architectural risks, clarify tradeoffs, and make decisions that balance speed, quality, maintainability, and long-term leverage.
• Raise the engineering bar through design reviews, code reviews, technical documentation, operational standards, and effective development practices.
• Mentor and develop engineers across teams, particularly in AI-assisted development, context engineering, evaluation design, system reliability, and agentic workflows.
• Use agentic coding tools such as Claude Code, Cursor, or equivalent to accelerate planning, implementation, testing, and review while maintaining strong standards for correctness, security, and maintainability.
• Ensure that systems are scalable, observable, secure, accessible, and economically sustainable in production.
• Contribute to engineering-wide discussions about responsible AI adoption, technical standards, platform capabilities, and organizational priorities.

Knowledge, Skills, and Abilities

• 10+ years of experience building and operating customer-facing software products.
• Demonstrated impact as a technical leader, staff engineer, principal engineer, tech lead, or equivalent role.
• Strong full-stack engineering fundamentals, including browser technologies, TypeScript, Node.js, PostgreSQL, cloud infrastructure, and distributed systems.
• Experience designing and delivering AI-powered products using LLMs, retrieval systems, evaluation frameworks, agentic workflows, or related technologies.
• A track record of leading complex initiatives that span multiple teams, systems, or organizational boundaries.
• Ability to set technical direction without relying on formal authority and to build alignment among engineers, product leaders, designers, and other stakeholders.
• Strong architectural judgment and the ability to communicate complex tradeoffs clearly to both technical and non-technical audiences.
• Experience creating durable engineering patterns, platforms, or capabilities that enable other teams to move faster.
• Product sensibility and a strong focus on user experience, quality, speed, and measurable outcomes.
• Comfort working in ambiguous environments where the problem, solution, and path to execut…