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About This Role
XPRIZE Overview
XPRIZE is an established global leader in designing and executing large-scale competitions to solve humanity’s greatest challenges. As a 501(c)3, our unique model democratizes innovation by incentivizing crowd-sourced, scientifically viable solutions to create a more equitable and abundant future for all. Since our founding in 1994, we’ve launched $519 million in prize competitions that are driving more than $31 billion in social and economic impact — a 60x return on philanthropic investment. These competitions not only de-risk early-stage breakthrough ideas but also mobilize capital, talent, and momentum to accelerate solutions from concept to real-world scale.
We operate across 5 areas of impact, including:
- Deep Tech + Exploration
- Energy + Climate + Nature
- Food + Water + Waste
- Health
- Learning + Society
Project Description
XPRIZE is seeking an experienced AI-Native Software Engineer to support the build of our new Prize Execution Platform — a unified system replacing our current, fragmented set of tools and expanding significantly on what they do today. The platform will manage the full lifecycle of an XPRIZE competition in a single ecosystem connecting four core user groups:
- XPRIZE staff, who design and configure competitions, manage milestones and timelines, oversee submission intake, coordinate judging, and track prize disbursement.
- Competitors, who register teams, submit applications and milestone deliverables, track their progress through the competition lifecycle, and receive AI-assisted matchmaking with relevant mentors.
- Judges, who review and score submissions — supported by AI-assisted scoring and automated submission review tools that surface relevant context and flag issues before human review.
- Alumni, who stay connected to the XPRIZE ecosystem post-competition through community and continued-engagement features.
AI is embedded directly into the product, not just the development process. Core AI-powered capabilities include:
- AI-assisted judging and scoring to support judges with consistent, efficient evaluation.
- Automated submission review to pre-screen and triage incoming applications and deliverables.
- Competitor-mentor matchmaking to connect competing teams with relevant subject-matter mentors.
- An applicant-facing chatbot to answer questions and guide competitors through the application and submission process.
This is a net-new platform, not a like-for-like migration — it will consolidate and significantly extend the capabilities of XPRIZE's current tooling. The engagement will be built using spec-driven and AI-assisted development practices on a .NET, Angular/React, and Python stack.
The ideal consultant can move quickly within a defined scope, work independently with minimal ramp-up, and deliver production-quality results on a set timeline — while also helping XPRIZE's internal engineering team build lasting capability in AI-assisted and spec-driven development practices.
Scope of Work:
- Design, develop, and deliver features and modules across the Prize Execution Platform, including competition management, submission intake, judging/scoring, competitor and mentor matchmaking, and applicant-facing AI tools within the defined project scope, using .NET, Angular/React, and Python as needed.
- Collaborate with the internal product and engineering team to confirm requirements, milestones, and acceptance criteria for the engagement.
- Deliver clean, maintainable, and tested code that meets the quality, security, and testing criteria defined in the Statement of Work and the technical guidelines provided at kickoff.
- Submit work product for XPRIZE review at agreed milestones, and join technical planning and review sessions as needed to confirm requirements and acceptance criteria.
- Use AI-assisted development tools (e.g., Claude Code, GitHub Copilot, or similar) as the primary development workflow — for scaffolding, refactoring, test generation, debugging, and documentation.
- Apply AI-first, spec-driven development practices, translating specifications into AI-assisted implementation, and document this workflow so it's reusable by the internal team after the engagement ends.
- Evaluate and refine AI-generated code for correctness, security, and architectural fit.
- Transfer knowledge to XPRIZE's internal engineers — including training on AI-assisted and spec-driven development methods used on this project — as part of project deliverables.
- Deliver clear technical documentation enabling the internal team to maintain and extend the solution post-engagement.
Qualifications:
- Bachelor's degree in Computer Science, Computer Engineering, or equivalent experience.
- Minimum 4 years of hands-on experience developing full stack web applications, including prior consulting/contract engagements.
- Demonstrated ability to ramp up quickly on an existing codebase and deliver independently within a defined scope and timeline.
- Hands-on experience using AI coding tools such as Claude Code, GitHub Copilot, Cursor, or similar in a professional workflow, with concrete examples of impact on delivery speed and quality.
- Demonstrated experience with AI-first, spec-driven development, with the ability to teach this approach to an internal team as part of a knowledge-transfer deliverable.
- Ability to critically evaluate AI-generated code for security, performance, and architectural consistency.
- Strong proficiency in .NET technologies and Python.
- Proven experience with Angular (v12+) or React w/ TypeScript.
- Solid understanding of HTML5, CSS3, JavaScript, and TypeScript.
- Proficiency with SQL Server or other relational database systems.
- Familiarity with Azure, Git, and CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, or similar).
- Able to deliver the milestones in the Statement of Work within the engagement timeline.
- Excellent problem-solving, communication, and collaboration skills; comfortable working independently with minimal day-to-day oversight.
Work Arrangement
This is a fully remote engagement. The consultant may work from any location within the United States, subject to applicable tax and legal requirements. The consultant determines when and where the work is performed. The consultant will attend milestone reviews and collaboration sessions, which are scheduled by mutual agreement and are expected to occur approximately 2-3 times per week. The consultant is expected to be reasonably responsive to XPRIZE team communications during U.S. Pacific business hours. Expected effort is approximately 30-40 hours per week, not to exceed 40 hours without written approval.
Tools and Access
XPRIZE will provide access to the AI-assisted development tools, repositories, cloud environments, and accounts needed for this engagement (including Claude Code, GitHub, Azure etc.). To protect XPRIZE data and systems, the consultant will use XPRIZE-provided tools and environments for all work involving XPRIZE code, data, or confidential information, and will not input XPRIZE confidential information into unapproved AI tools or services. The consultant is responsible for providing their own computer, internet connection, and general office equipment. Access will be revoked at the end of the engagement.
Intellectual Property and Confidentiality
All work product created under this engagement, including code, documentation, specifications, prompts, workflows, and training materials, will be owned by XPRIZE and assigned to XPRIZE under the consulting agreement. The consultant will be required to sign a confidentiality agreement and IP assignment before starting work.
Independent Contractor Status
The consultant will be engaged directly by XPRIZE as an independent contractor and will receive IRS Form 1099. The consultant is not an employee of XPRIZE and is not eligible for employee benefits, including health insurance, retirement plans, or paid time off. The consultant is responsible for their own taxes, insurance, and business expenses. The consultant controls the means and methods of their work, within the scope, milestones, and acceptance criteria agreed in the Statement of Work.
Compensation
$75-85/hour based on skills and experience
Please note: Submitting a resume or proposal does not make you a candidate for engagement. You will be considered a candidate only after XPRIZE contacts you directly to begin the engagement process, which may include interviews, a technical assessment, reference checks, and a background check where permitted by law. Final engagement is contingent on execution of a written independent contractor agreement, including confidentiality and IP assignment terms. XPRIZE is an equal opportunity organization and considers all qualified individuals regardless of race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other legally protected characteristic.
Note: if you experience any issues or errors while trying to submit your application, please try clearing your cache and cookies or applying through a different browser (for example, Safari instead of Google Chrome).
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Salary Context
This $156K-$176K range is below the median for AI Software Engineer roles in our dataset (median: $194K across 269 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 11,520 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At XPRIZE Foundation, 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 $220,000 based on 1,688 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($166K) sits 24% below the category median. Disclosed range: $156K to $176K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
XPRIZE Foundation AI Hiring
XPRIZE Foundation has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US. Compensation range: $176K - $176K.
Remote Work Context
Remote AI roles pay a median of $188,200 across 2,430 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, 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 $266,050 median, while Prompt Engineer roles sit at $140,000. 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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