Lead Software Engineer, AI

Remote Senior AI Software Engineer

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Skills & Technologies

AnthropicAzureClaudeOpenaiTypescript

About This Role

AI job market dashboard showing open roles by category

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 execution must be shaped collaboratively.
  • High ownership mentality, with the ability to move between strategy, architecture, implementation, and operational follow-through.
  • Experience mentoring engineers and strengthening engineering practices across a team or organization.
  • Commitment to building reliable, secure, observable, and cost-effective AI systems.
  • Thrives in a remote, async-first environment with a lean, high-output team.
  • Experience working at a startup or organization with a high engineering bar and a bias toward meaningful, measurable impact.

Working Conditions & Hiring Process

  • U.S. Work Location Requirement: All employees must reside in and perform work within the United States. We do not support international remote work arrangements for this role.
  • Travel Expectations: While this is a remote position, occasional travel may be required for team meetings, company events, conferences, summits, and similar activities. Candidates must be willing and able to travel as needed.
  • On-Camera Work Environment: We operate in a highly collaborative, remote, on-camera culture. Employees are expected to be on camera during meetings unless extenuating circumstances apply.
  • Recorded Video Interviews: All video interviews conducted during the hiring process will be recorded to support internal hiring consistency and process improvement.
  • Background Checks: Employment with Penn Foster Group is contingent upon successfully completing applicable pre-employment screening requirements, which may include verification of employment history, education, and criminal background, where permitted by law.
  • Identity Verification (Form I-9): As part of our onboarding process, all hires must complete employment eligibility verification in compliance with federal law. This includes remote Form I-9 verification, which may require an in-person identity verification step with an authorized representative.

About Us

At Penn Foster Group, we are transforming online learning to help learners by uniting Penn Foster, CareerStep, Ashworth College, James Madison High School, the New York Institute of Photography, the New York Institute of Art and Design, and other education platforms. Together, we create an accelerated path to greater economic mobility through real-world skills and knowledge that enable learners to achieve long-term success.

Our history dates back to 1890, when our founder, Thomas Foster, pioneered distance education by offering training by mail for coal miners to gain the skills needed for safer jobs. Today, with the partners who use our education and training programs, we continue that mission by providing accessible training and education for in-demand skills and building a workforce prepared for the future job market.

Equal Employment Opportunity

We strive toward Diversity, Equity, and Inclusion at Penn Foster Group by intentionally building teams that are diverse in identities, lived experiences, and ideas, creating a culture where people feel connected to each other and have a sense of belonging. We value diversity, equity, and inclusion because they enable us to maximize the number of learners who reach their goals, deliver the experiences we want them to have, and become the kind of company we want to work in.

What We Offer

We offer a robust benefits package that includes medical, dental, vision, flexible spending, generous paid time off, sponsored volunteer opportunities, a 401(k) with a company match, and free access to all of our online programs.

Role Details

Title Lead Software Engineer, AI
Location Remote, US
Category AI Software Engineer
Experience Senior
Salary Not disclosed
Remote Yes

About This Role

AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.

The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.

Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Penn Foster Group, this role fits into their broader AI and engineering organization.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

What the Work Looks Like

A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

Skills Required

Anthropic (2% of roles) Azure (8% of roles) Claude (5% of roles) Openai (3% of roles) Typescript (3% of roles)

Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.

Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.

Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

Compensation Benchmarks

AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

Penn Foster Group AI Hiring

Penn Foster Group has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US.

Remote Work Context

Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.

Career Path

Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.

From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.

If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.

What to Expect in Interviews

Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.

When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

AI Hiring Overview

The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

The AI Job Market Today

The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 1,601 roles with disclosed compensation, the median salary for AI Software Engineer positions is $220,000. Actual compensation varies by seniority, location, and company stage.
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Penn Foster Group is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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