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About This Role
About Us
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Circle is building the world's leading all\-in\-one platform for online communities. We make it possible for creators, coaches, educators, and businesses to bring together their audience with engaging discussions, live streams, events, chat, courses, and payments — all in one place, all under their own brand.
We're proud to be a fully remote company of around 200 (and growing!) team members from 30\+ countries around the world. We seek exceptional individuals around the world, set them up to do the best work of their lives, and in turn, create a meaningful impact in their own lives. We don't track hours, but we do manage for high expectations very closely. We collaborate across time zones, are highly async, and like to document a lot.
Twice a year, we bring the whole company together in beautiful places around the world for our company offsites. So far, we've hosted offsites in Turkey, Portugal, Mexico, Thailand, Colombia, Italy, Ireland, and more, with still more to come!
Check out our Careers page for more about working at Circle.
About the role
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The Applied AI team at Circle is at the forefront of leveraging AI to drive innovation for our customers through transformative applications of large language models (LLMs).
We're looking for a strong full\-stack engineer who is proficient in web frameworks, backend development, and infrastructure to spearhead the development of full\-stack AI solutions across Circle. You will work on exciting projects such as AI agents, Retrieval\-Augmented Generation, AI evaluations and observability, and building infrastructure for LLM inference.
While deep AI specialization or expertise isn't required, we care about some hands\-on experience building AI features. Beyond that, we're looking for a strong experimentation mindset. If you're excited about rapidly testing ideas, running A/B experiments, and iterating on real production use cases of LLMs, this role is for you.
The Applied AI team is composed of different backgrounds. Some team members joined with deep Rails experience and solid AI fundamentals, while other team members joined with deep AI experience and ramped up on Rails. Either path works as long as you bring hands\-on experience with both Rails and AI and have genuine curiosity to grow.
What you'll be doing
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- Ship full\-stack AI projects end\-to\-end on a product built in Ruby on Rails backend and React frontend.
- Design and run experiments (including A/B tests, AI evaluations, or others) to validate AI features, measure impact, and guide iteration.
- Build and integrate components for AI infrastructure and optimize them for performance and reliability to support production\-level inferencing.
- Improve processes, tools, and systems to scale AI features into production\-ready solutions.
- Help us stay up\-to\-date with the cutting\-edge AI research, techniques, and tools.
- Work closely with Circle's leaders and designers throughout the feature design process.
- Foster a bias for action by prioritizing speed of iteration, experimentation, and learning, while maintaining high standards of code quality and user experience.
What you'll need to be successful
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- 6\+ years experience working as a full\-stack engineer on high\-traffic production applications. You've dealt with the challenges that come with scale — query optimization, careful migrations, performance bottlenecks.
- Strong proficiency in Ruby on Rails, MySQL / Postgresql, ReactJS. Familiarity with both frontend and backend is necessary, but a high degree of proficiency in both is not a requirement.
- Hands\-on experience building AI features in production — whether RAG systems, AI agents, or LLM\-powered tools. You've shipped at least one real AI use case, not just prototypes.
- Strong experimentation mindset — you're comfortable designing and running A/B tests, measuring results, and iterating quickly to discover what works and what doesn't.
- A desire to work in an environment which values speed of iteration and individual autonomy, while also embracing personal accountability and the ability to collaborate effectively as part of a dynamic team.
- Comfortable in a fast\-paced environment with a certain level of ambiguity, especially when learning and picking up new technologies when projects require it.
- Strong alignment with our values, find our values on our career page if you haven't read up on them yet.
- You are proficient in English (spoken, written, and reading) at a CEFR Level C2 / ILR Level 5.
$130,000 \- $140,000 USD per year
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Circle offers U.S.\-benchmarked compensation globally, equity in the company with ongoing refresh grants, and 35 days of paid time off each year.
We're a remote\-only team that comes together twice a year for company retreats in incredible destinations around the world. Alongside incredible flexibility and autonomy, we offer a benefits package that supports health, wellbeing, and professional growth. Learn more in our Candidate Hub.
Learn more
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- Candidate Safety \& Interview Process Notice
- Diversity, Equity \& Inclusion
- How We Use Candidate Data
- Equal Employment Opportunity
- Visit our Candidate Hub to learn more about working at Circle, our benefits, and our hiring process.
Salary Context
This $130K-$140K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Circle.so, 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 $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($135K) sits 38% below the category median. Disclosed range: $130K to $140K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Circle.so AI Hiring
Circle.so has 1 open AI role right now. They're hiring across AI Software Engineer. Based in New York, NY, US. Compensation range: $140K - $140K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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