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About This Role
About Sprig
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Sprig is the customer survey platform, rebuilt around AI agents.
For two decades, teams have relied on Qualtrics, Medallia, and SurveyMonkey to understand their customers. These platforms were built for a slower era, with manual setup, fragmented workflows, and insights that arrive too late to share decisions. The gap between how fast products move and how fast research can keep up has never been wider.
We're building something different. With Sprig, AI agents design studies, adapt surveys in real time, and turn responses into clear, actionable insight. Teams move from question to evidence in hours instead of weeks, without sacrificing rigor. Product teams no longer guess. They know.
Our mission is to make deep customer understanding effortless and always on, so the best teams in the world can build products their customers love.
Companies like Microsoft, DoorDash, Notion, Figma, Coinbase, and TripAdvisor use Sprig to stay close to their users. Backed by $85M from Andreessen Horowitz, Accel, and First Round Capital, we're growing quickly across the world's leading product organizations.
The category is being rebuilt, with AI at the core. If you're excited by hard problems and the chance to define how modern teams understand their customers, we'd love to meet you.
About the Role
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Sprig’s AI team builds the systems that help user\-experience researchers and product managers understand their users at scale. Every day, we process over half a billion events and run millions of AI inference queries, transforming raw feedback and usage data into actionable product insights. As a senior software engineer, you’ll own and evolve the backend systems that make this possible—distributed data pipelines, inference workflows, and the integrations that bring AI\-powered understanding into Sprig’s product. Our work spans from distributed data processing and inference pipelines to the product surface that UX researchers and PMs interact with. The team operates across the stack but this role emphasizes large\-scale backend systems and integration with applied AI. You’ll join a group that values pragmatic engineering, clear design, and measurable impact, advancing both our technical foundation and our ability to deliver trustworthy, privacy\-safe analyses and insights.
This is a hybrid role with three days working in our downtown San Francisco office, which is just a short walking distance from the Montgomery BART station.
Your Impact
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- Build and ship features – Develop backend APIs and AI flows that help product and research teams understand user experiences at scale.
- Own small features end\-to\-end – Take responsibility for well\-defined product features, from design and implementation to monitoring and iteration.
- Collaborate and learn from experienced engineers – Work closely with senior teammates to review designs, debug complex issues, and improve your technical judgment.
- Extend across the stack – while the focus is backend, contribute where needed in the full stack, supporting product surfaces that bring AI analyses and insights to life.
- Contribute to quality and shared understanding – Write reliable, testable code, improve observability, and document designs so others can build confidently on your work.
Your Strengths
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- Experience – You have 2\+ years of professional experience building and shipping production software.
- Product\-minded – Care deeply about usability and product outcomes, not just system correctness. You think about how your work enables better customer experiences.
- Comfortable with or ready to switch to TypeScript – You’ll use TypeScript for most development. Familiarity with technologies like Node.js, Temporal, AWS, or PostgreSQL is a plus. If your main experience is in python or other languages, it is ok if you’re ready to switch to working primarily in TypeScript.
- Fundamentals – You have a solid understanding of data structures, RESTful APIs, SQL, and testing.
- Communicator – You communicate clearly, contribute to reviews and design discussions, and learn through feedback.
- Growth minded – You are motivated to extend skills into distributed AI workflows, inference systems, and prompt and context engineering.
Benefits \& Perks
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- Competitive Salary
- Competitive Employee Equity
- 401K Program
- Medical, Dental, and Vision Benefits
- FSA/HSA Benefit
- $175/month Commuter Benefit
- Additional Wellbeing Benefits
- Flexible Paid Time Off
- Paid Parental Leave
- Professional Development Stipend
- Hybrid Office Policy
- Lunch and dinner daily
- Company Sponsored Social Events
At Sprig, we pride ourselves on being a people\-first company where your contributions matter and your impact is visible. We’ve been recognized as a Great Place to Work for three consecutive years and have also been named one of Fortune’s Best Workplaces in the Bay Area and one of Built In’s Best Places to Work. If you're excited about helping build products that millions of users love while shaping the future of AI\-powered user research, we'd love to meet you.
Our Commitment to Diversity and Inclusion
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We prioritize diversity within our team and value different perspectives, educational backgrounds, and life experiences. We encourage people from underrepresented backgrounds to apply.
Employee Pay Disclosure
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The salary range for this full\-time position is $150,000\- $230,000 \+ Equity \+ Benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all locations (San Francisco, CA; New York, NY). Within the range, individual pay is determined by work location and additional factors, including job\-related skills, experience, and relevant education or training. Your Recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in postings reflect the base salary only, and do not include equity or benefits.
\*\*\*Please beware of scammers who are posing as Sprig and Sprig team members. Our recruiters use @sprig.com email addresses exclusively. We do not conduct interviews via text or instant message, and we do not ask candidates to purchase equipment through us or solicit money from you. If you have been contacted by someone claiming to be from a different domain about a job offer, please report it as potential job fraud to law enforcement and contact us here.\*\*\*
Salary Context
This $150K-$230K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 219 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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Sprig, 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 $232,000 based on 797 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($190K) sits 18% below the category median. Disclosed range: $150K to $230K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Sprig AI Hiring
Sprig has 1 open AI role right now. They're hiring across AI Software Engineer. Based in San Francisco, CA, US. Compensation range: $230K - $230K.
Location Context
AI roles in San Francisco pay a median of $253,000 across 2,168 tracked positions. That's 26% 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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