Interested in this AI Software Engineer role at PEBL?
Apply Now →Skills & Technologies
About This Role
Purpose in Every Position
Pebl puts a world of talent at your fingertips. With our AI\-powered Global Work Platform, companies can hire, pay, and manage employees in 185\+ countries—removing risk, red tape, and guesswork from global growth. Backed by more than a decade of compliance leadership and local expertise, Pebl helps businesses move fast, stay compliant, and scale with confidence. With Pebl, companies everywhere can hire great talent anywhere.
Where Your Work Moves the Needle.
At Pebl, every team member drives our success. Joining us means more than filling a role—you’re accountable for results and impact. Our values guide how we operate, execute, and collaborate across borders. By putting them into action, you’ll help us scale faster, compete harder, and lead the future of global work.
What Makes You a Great Fit
Our mission at Pebl is to simplify global employment, enabling companies to hire, manage, and retain talent anywhere in the world. We’re not just adding a chatbot to our product — we’re rethinking what it means for software to work with you, not just for you. Our AI \& Knowledge team is on the front lines of that shift, building Alfie, our conversational AI assistant, and we’re looking for a Senior Full\-Stack Software Engineer who wants to help define what AI\-native user experience looks like — not follow a playbook that already exists, because it doesn’t yet.
We’re looking for someone who is strongest in frontend/product engineering and excited about building conversational AI interfaces that real users interact with directly. You’ll help shape the experience around streaming responses, wrong\-answer recovery, fallback states, user trust, and human\-in\-the\-loop moments.
This is not primarily a backend AI infrastructure, RAG platform, internal automation, or AI\-assisted developer tooling role; the core need is someone who can help drive the user\-facing AI experience.
*This role will require in\-office collaboration Monday\-Wednesday in our Palo Alto, CA office.*
How You’ll Make an Impact
- Design and build full\-stack features for our conversational AI assistant, with particular depth and ownership on the frontend/UX side.
- Apply hands\-on experience with LLM\-based and agentic systems — prompt design, tool/function calling, multi\-step agent reasoning, evaluation — to shape both how the assistant behaves and how that behavior surfaces in the UI.
- Bring product taste and a strong point of view on what makes an AI\-driven experience great — push for a better UX rather than shipping “good enough.”
- Push the boundaries of what conversational and generative AI interfaces can feel like — prototype and propose new interaction patterns as the underlying models and agent capabilities evolve.
- Help shape the future of how people interact with software at Pebl — you’ll be working at the edge of what’s possible in conversational and agentic UX, not maintaining what’s already been figured out.
- Build and maintain both frontend and backend components (TypeScript/React on the frontend; comfortable enough on the backend to design clean contracts and APIs that support agentic workflows).
- Lead by example in clean, maintainable code across the stack; mentor junior team members and foster a culture of constant learning and improvement.
- Contribute to technical discussions, design reviews, and code reviews to maintain high engineering standards.
- Troubleshoot issues end\-to\-end (frontend and backend) in production, including AI\-specific failure modes (e.g., bad model output, latency, dropped tool calls).
Let’s Connect If You Have
- 8\+ years of professional software engineering experience, full\-stack, with demonstrated strength and a clear preference for frontend/UX work.
- 1\+ years of hands\-on experience building LLM\-powered or agentic products — not just calling an API, but designing how an agent reasons, uses tools, and hands control back to the user.
- Experience building interfaces for AI\-powered or agentic products — conversational UIs, copilots, assistants — including exposure to generative/dynamic UI techniques where the interface adapts to model behavior.
- Solid understanding of LLM design patterns, prompt engineering, and observability/instrumentation for agentic systems.
- Strong command of modern frontend (React/TypeScript) paired with a solid understanding of how frontends integrate with backend services, APIs, and real\-time/streaming data.
- A track record of helping build products beyond standard CRUD apps and dashboards — something with real craft, polish, or a distinctive user experience.
- Comfort working across the full stack when needed (backend, infra) — this isn’t a pure frontend role.
- A lean mindset — focus on delivering customer value by minimizing waste, optimizing workflows, fostering continuous improvement, and prioritizing quick iteration with quick feedback cycles.
- Excitement for working in a space that’s evolving rapidly, where the best patterns for AI\-driven UX are still being discovered — and a desire to help discover them.
Our Commitment to You
At Pebl, we’re committed to supporting our team with comprehensive rewards and benefits designed to meet diverse needs across roles and locations. Our core offerings include:
- Flexible Time Off – Take the time you need to recharge.
- Parental Leave – Support for growing families.
- Health and Dental Insurance – Where applicable, to cover you and your loved ones.
- Retirement Savings \+ Employee Incentive Plan – Plan for the future while sharing our success.
Please visit our career page for more information.
Pebl is an Equal Opportunity Employer.
We power global teams and believe diverse perspectives drive innovation and impact. Employment decisions at Pebl are based on qualifications, merit, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable law. We’re committed to fostering an inclusive culture where every teammate can thrive and do the best work of their career—anywhere in the world.
Compensation Range: $145\.6K \- $172\.9K
Salary Context
This $145K-$172K range is below the median 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 PEBL, 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 ($159K) sits 27% below the category median. Disclosed range: $145K to $172K.
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.
PEBL AI Hiring
PEBL has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Palo Alto, CA, US. Compensation range: $172K - $172K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.