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About This Role
About Us
Our leading SaaS\-based Global Employment Platform™ enables clients to expand into over 180 countries quickly and efficiently, without the complexities of establishing local entities. At G\-P, we're dedicated to breaking down barriers to global business and creating opportunities for everyone, everywhere.
Our diverse, remote\-first teams are essential to our success. We empower our Dream Team members with flexibility and resources, fostering an environment where innovation thrives and every contribution is valued and celebrated.
The work you do here will positively impact lives around the world. We stand by our promise: Opportunity Made Possible. In addition to competitive compensation and benefits, we invite you to join us in expanding your skills and helping to reshape the future of work.
At G\-P, we assist organizations in building exceptional global teams in days, not months—streamlining the hiring, onboarding, and management process to unlock growth potential for all.
G\-P helps organizations build global teams in minutes, not months. As part of this mission, we've created an indispensable AI agent for HR leaders, G\-P Gia™ .
Gia is our AI\-powered global HR agent that provides HR compliance guidance instantly. Built on over a decade of global employment and legal expertise and 100,000\+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.
About this Position
We are hiring a hands\-on technical leader to raise the engineering bar across our teams.
You will partner with Engineering Managers and senior engineers to improve architecture, technical design, code reviews, CI/CD, infrastructure, and engineering practices. You will also remain an active individual contributor, shipping production code and leading technically complex initiatives.
This is not a traditional architect role focused on diagrams and approvals. You will build systems, create practical engineering guardrails, and help teams make better technical decisions without becoming a bottleneck.
What you will do:
- Define and evolve architecture and engineering practices across multiple teams.
- Partner with Engineering Managers and technical leads on complex system\-design decisions.
- Lead technical designs, RFCs, architecture reviews, and critical code reviews.
- Build and ship production systems across AI, backend, cloud, infrastructure, and full\-stack applications.
- Improve CI/CD, testing, observability, reliability, security, and developer experience.
- Create reusable platforms, libraries, reference implementations, and paved roads for teams.
- Help design and operate production AI systems, including model integration, orchestration, retrieval, evaluation, and monitoring.
- Contribute to cloud infrastructure and help resolve complex production issues.
- Mentor engineers and raise technical quality through hands\-on leadership.
- Ensure engineering standards remain effective after they are introduced.
What we are looking for:
*Minimum Requirements:*
- 15\+ years of experience in architecture.
- Founding Engineer experienced with scaling startups.
- Ability to influence multiple teams without relying on formal authority.
- Resourceful and Independent to own and operate across teams and individual projects.
- Strong experience designing, building, and operating production software systems.
- Deep expertise in AI systems, backend or distributed systems, infrastructure and cloud architecture.
- Practical understanding of modern AI systems, including foundation models, inference, retrieval, orchestration, evaluation, latency, and cost.
- Strong working knowledge of full\-stack development.
- Experience with Python, Go, TypeScript, Kubernetes, and major cloud platforms.
Preferred Qualifications:
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What Success Looks Like
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- Lead the engineering transformation to turn adhoc features into scaled robust systems
- Setup practices for Release Lifecycle.
- Improve the quality and consistency of technical design across teams.
- Establish engineering guardrails that teams actually use.
- Reduce repeated architectural mistakes and unnecessary duplication.
- Improve developer velocity, reliability, and operational quality.
- Become a trusted technical partner to Engineering Managers and senior engineers
The annual gross base salary range for this position is $180,000 \- $225,000 plus variable compensation.
Our ranges are established using objective market benchmarking data for this level of work. Final placement within the range is determined by gender\-neutral criteria, including the candidate's relevant skills, experience, and specific qualifications for the role.
Actual compensation for this position may vary and will depend on multiple factors such as relevant qualifications, experience, education, and geographic location. For Full\-Time Regular Employees, this position is also eligible for additional compensation as follows:
- Sales Roles: This position is eligible for a commission structure in addition to base salary.
- Non\-Sales Roles: This position is eligible for an annual bonus which is paid dependent on various factors, including and without limitation, individual and company performance in addition to base salary.
Benefits
G\-P values its employees and offers excellent benefits and perks including generous paid parental leave, flexible time off, spending accounts, medical insurance, dental insurance, vision insurance, sabbatical after 5 years and more.
*Individuals residing, or applying to work, in the**United States: California or Philadelphia,Pennsylvania,**please review the following additional information:*
*G\-P will consider qualified applicants with arrest or conviction records in accordance with the California Fair Chance Act, Los Angeles City Fair Chance Act Ordinance, Los Angeles County Fair Chance Act Ordinance, and San Francisco Fair Chance Act Ordinance. Los Angeles applicants can review additional information regarding the Los Angeles City Fair Chance Act here:Fair Chance Initiative for Hiring Ordinance, and Philadelphia applicants can review information pertaining to Philadelphia's Fair Criminal Record Screening Standards Ordinance here:Fair Chance Poster. Any consideration of a candidate's background check with arrest or conviction records will include an individualized assessment based on the factors required by applicable law, including the candidate's specific record and the duties and requirements of the specific job.*
G\-P. Global Made Possible.
*G\-P is a proud Equal Opportunity Employer, and we are committed to building and maintaining a diverse, equitable and inclusive culture that celebrates authenticity. We prohibit discrimination and harassment against employees or applicants on the basis of race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, and pregnancy\-related conditions), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other legally protected status.*
*G\-P also is committed to providing reasonable accommodations to individuals with disabilities. Individuals with disabilities are encouraged to apply for these positions. If you need an accommodation due to a disability during the interview process, please contact us at* *careers@g\-p.com.*
Salary Context
This $180K-$225K range is above the median 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 G-P, 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 ($202K) sits 7% below the category median. Disclosed range: $180K to $225K.
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.
G-P AI Hiring
G-P has 2 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Based in Seattle, WA, US. Compensation range: $225K - $225K.
Location Context
AI roles in Seattle pay a median of $228,700 across 516 tracked positions. That's 6% above the national median.
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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