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About This Role
ABOUT KION
Kion is revolutionizing CloudOps and FinOps. We offer a unified approach, delivering multicloud, multi\-org, and multi\-account visibility and controls, empowering organizations to effectively manage their complex cloud environments from a single, centralized platform. At Kion, you’ll join a team that values collaboration, creativity, and building products that make a real impact for customers across industries.
We’re a fast\-growing, Series A startup and we believe employees are our most precious resource. While we’re headquartered outside Baltimore, MD and Washington DC, we are committed to a 100% remote\-first workforce. In addition, Kion offers excellent compensation and outstanding benefits!
If you're passionate about using your expert skills to bring transformational change to a customer’s cloud journey, you'd be a great addition to our team!
ABOUT THE ROLE
We’re seeking a Senior Software Engineer to join our growing team and help evolve our core product. You’ll work closely with designers, product managers, and fellow engineers to deliver features that empower our customers to manage cloud environments more efficiently and securely.
YOUR DAY\-TO\-DAY:
- Collaborate with designers and product managers to transform ideas into user\-friendly solutions.
- Develop AI\-powered product capabilities.
- Build and integrate Model Context Protocol (MCP) servers, clients, and tools that connect AI models with Kion data and capabilities.
- Establish evaluation and observability practices for AI features, including accuracy, relevance, hallucination risk, token usage, latency, and customer impact.
- Contribute to architectural decisions across the application.
- Build and maintain scalable front\-end components and API services.
- Contribute to architectural decisions across the stack (Angular front\-end, Go backend).
- Improve code quality, usability, and extensibility through thoughtful engineering practices.
- Participate in planning, estimation, and scoping for new features and enhancements.
- Partner with cross\-functional teams to ensure a smooth development lifecycle and high\-quality deliverables.
- Own the planning, development, testing, and delivery of a feature from end\-to\-end.
WHAT WE ARE EXPECTING FROM YOU (I.E., THE QUALIFICATIONS YOU MUST HAVE):
- 5\+ years of professional experience building scalable web applications.
- Familiarity with MCP or similar protocols and patterns for connecting AI models to tools, data, and application services.
- Understanding of common AI application risks, including hallucinations, prompt injection, data leakage, access control, and unpredictable model behavior.
- Proficiency with a modern front\-end framework (e.g. Angular, React, or Vue).
- Experience with back\-end development (e.g. Go, Java, Python, Ruby, Node.js, C\#).
- Production experience designing, building, and integrating with APIs.
- Strong knowledge of relational databases (e.g., MySQL, PostgreSQL) and API design.
- Familiarity with major cloud providers (AWS, Azure, or GCP).
- Ability to plan and own features end\-to\-end and collaborate effectively in Agile teams.
- Experience working with ambiguity in a fast\-paced development environment.
BONUS POINTS (Not required—if you don’t have them, please still apply!):
- Degree in Computer Science or related field—or equivalent practical experience.
- Experience with Angular, and Golang.
- Exposure to multi\-cloud and virtualized environments or cloud tooling.
- Demonstrated experience shipping AI or LLM\-powered features into production, beyond proofs of concept.
- Hands\-on experience with LLM APIs and concepts such as prompt design, structured outputs, tool calling, context management, and model evaluation.
- Experience developing FinTech solutions.
WHAT WE WILL PROVIDE IN RETURN:
- Remote\-first Culture: Work anywhere in the U.S. with flexible hours (US only)!
- Inclusive and Collaborative Environment: We value diverse perspectives and believe great ideas come from everywhere. Our teams are small, allowing for a collaborative environment that fosters communication and innovation.
- Excellent Compensation and Outstanding Benefits: Including medical, dental, vision, unlimited PTO, and 401(k) contribution.
- Growth Opportunities: Build cutting\-edge cloud solutions with room to explore new technologies and career paths.
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 Rippling, 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.
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.
Rippling AI Hiring
Rippling has 12 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager, AI Agent Developer. Positions span Melville, NY, US, Columbia, MD, US, Remote, US. Compensation range: $130K - $350K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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.
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