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About This Role
About GitHub: GitHub is the world’s leading platform for agentic software development — powered by Copilot to build, scale, and deliver secure software. Over 180 million developers, including more than 90% of the Fortune 100 companies, use GitHub to collaborate, and more than 77,000 organisations have adopted GitHub Copilot.
Locations: In this role you can work from Remote, United States
Overview:
GitHub is looking for a Staff Software Engineer to join the Enterprise AI Governance team. Together with a distributed, diverse and passionate team of engineers and designers, you will build the platforms, services, and controls that help customers securely configure, govern, and operate Copilot experiences at scale. In this role you will design, prototype, implement, ship and support highly performant and inspiring systems with your team.
You will architect and build highly available, secure backend services and APIs that give customers fine\-grained control and visibility over how Copilot is deployed across their organizations, from policy enforcement to auditing to configuration management. The ideal candidate has deep experience designing distributed systems that must balance security, compliance, and scale, and enjoys solving problems where trust and governance are first\-class product requirements, not afterthoughts.
As a Staff Software Engineer, you will lead technical direction across the Enterprise AI Governance team, setting the bar for system design, reliability, and operational excellence. You'll partner closely with product, security, and other Copilot platform teams to ensure governance capabilities scale alongside Copilot's rapid growth, while remaining simple and trustworthy for enterprise customers to adopt.
We are looking for creative problem solvers and diverse thinkers, people who care about culture as well as customers and features. We believe that how we do things is as important as what we do. Big vision, a common purpose, passion for quality, curiosity, dedication, and investment in fun and collaboration are what lead to great results. Great products reflect the teams that build them.
Responsibilities:
- Design, develop, test, and ship high\-quality technical solutions that scale across GitHub services, staying intimately familiar with the systems you build and taking pride in maintainable code.
- Provide technical leadership, mentorship, pairing, and code reviews that grow others and help teams produce extensible, maintainable code that integrates cleanly with downstream dependencies and meets quality standards.
- Own and advocate for the health and quality of the systems the team builds, including participating in on\-call and first\-responder rotations.
- Write architecture briefs and proposals, and run code experiments.
- Design and implement APIs that enable seamless integration between software components.
- Use CI/CD tools to build automated pipelines for continuous integration and delivery.
- Collaborate with cross\-functional teams and stakeholders, leading discussions on technical solutions, including design and cost tradeoffs.
- Create and guide others in developing testing plans, defining success metrics, and integrating customer feedback, ensuring quality, reliability, and continuous improvement while meeting security and compliance standards.
- Maintain executional and operational excellence within and across teams and organizations.
- Use debugging tools and telemetry to validate assumptions, proactively resolve issues, and optimize code performance and maintainability.
- Drive and support a technical roadmap aligned with product goals, prioritizing engineering efforts and adopting new technologies and methodologies where applicable.
Qualifications:
Required Qualifications:* 9\+ years experience in Software Engineering, Computer Science, or related technical discipline with proven experience maintaining and delivering production software coding in languages including, but not limited to, C, C\+\+, C\#, Java, JavaScript, Go, Ruby, Rust, or Python
+ OR Associate’s Degree in Computer Science, Electrical Engineering, Electronics Engineering, Math, Physics, Computer Engineering, Computer Science, or related field AND 8\+ years experience in Software Engineering, Computer Science, or related technical discipline with proven experience maintaining and delivering production software coding in languages including, but not limited to, C, C\+\+, C\#, Java, JavaScript, Go, Ruby, Rust, or Python
+ OR Bachelor's Degree in Computer Science or related field AND 7\+ years experience in Software Engineering, Computer Science, or related technical discipline with proven experience maintaining and delivering production software coding in languages including, but not limited to, C, C\+\+, C\#, Java, JavaScript, Go, Ruby, Rust, or Python
+ OR Master's Degree in Computer Science, Electrical Engineering, Electronics Engineering, Math, Physics, Computer Engineering, Computer Science, or related field AND 5\+ years experience in Software Engineering, Computer Science, or related technical discipline with proven experience maintaining and delivering production software coding in languages including, but not limited to, C, C\+\+, C\#, Java, JavaScript, Go, Ruby, Rust, or Python
+ OR Doctorate in Computer Science, Electrical Engineering, Electronics Engineering, Math, Physics, Computer Engineering, Computer Science, or related field AND 3\+ years experience in Software Engineering, Computer Science, or related technical discipline with proven experience maintaining and delivering production software coding in languages including, but not limited to, C, C\+\+, C\#, Java, JavaScript, Go, Ruby, Rust, or Python
+ OR equivalent experience.
- 2\+ years experience in technical leadership roles such as technical lead, team lead or equivalent.
Preferred Qualifications:* Hands\-on experience with modern front\-end technologies (e.g., React, CSS, HTML, JavaScript/TypeScript) and design systems.
- 1\+ years experience building agent\-based experiences on top of large language modes (LLM's) including prompt engineering, tool use, and agentic workflow design.
- 2 \+ years experience using general purpose programming languages (e.g., Go, Ruby, or similar).
- Demonstrated experience with large\-scale system architecture and design, particularly in cloud\-based environments, with a strong understanding of distributed systems and microservices.
- Experience working closely with product management, design, and other engineering teams to drive cross\-functional projects and deliver high\-quality products
Compensation Range: The base salary range for this job is USD $140,400\.00 \- USD $372,300\.00 /Yr.
These pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. At GitHub certain roles are eligible for benefits and additional rewards, including annual bonus and stock. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee's role.
This position will be open for a minimum of 3 days, with applications accepted on an ongoing basis until the position is filled.
GitHub Leadership Principles:
GitHub values
- Customer\-obsessed
- Ship to learn
- Growth mindset
- Own the outcome
- Better together
- Diverse and inclusive
Manager fundamentals
- Model
- Coach
- Care
Leadership principles
- Create clarity
- Generate energy
- Deliver success
Who We Are: GitHub is the world’s leading AI\-powered developer platform with 150 million developers and counting. We’re also home to the biggest open\-source community on earth (and 99% of the world’s software has open\-source code in its DNA). Many of the apps and programs you use every day are built on GitHub.
Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We’re remote\-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are—because we know that people flourish when they can work on their own terms.
Join us, and let’s change the world, together.
EEO Statement: GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!
Salary Context
This $140K-$372K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).
Role Details
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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At GitHub, 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
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 $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($256K) sits 17% above the category median. Disclosed range: $140K to $372K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
GitHub AI Hiring
GitHub has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US. Compensation range: $372K - $372K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
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