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About This Role
### Description
You'll join the team building Brivo's AI platform—the services, integrations, and guardrails that bring intelligent, natural\-language capabilities to our core Access Control and Video products. This is a hands\-on role where you'll write production code from day one, learn how large\-scale systems are built and operated, and grow alongside experienced engineers who will mentor you through design reviews, code reviews, and real production work. We're looking for someone curious, eager to learn, and excited about AI—someone who picks up new technologies quickly, asks good questions, speaks up, and thrives in a fast\-paced environment.
You will join a high\-impact team building the next generation of AI\-powered experiences on Brivo's platform. This team helps customers get more value from their access control and video systems by making buildings and their data intelligible and actionable through AI—working on capabilities ranging from LLM orchestration and safety guardrails to tools that let AI agents interact with the platform. You'll get broad exposure to modern backend, cloud, and AI engineering.### Responsibilities
- Spend the majority of your time coding. You'll build and maintain features in production API services using Node.js/TypeScript and Express, with support and mentorship from senior engineers.
- Contribute to our LLM and generative AI features—helping implement prompt logic, tool/function calling, and agent workflows—and learn how they run safely at scale.
- Help build and test AI safety guardrails (e.g., prompt\-injection and data\-exposure checks) and tooling that lets AI agents interact with the platform.
- Participate actively in code reviews and design discussions, learning to document decisions and raise the quality bar over time.
- Write and maintain automated tests (unit and integration) and help troubleshoot issues in development and production environments.
- Work within an Agile team—joining sprint planning, backlog grooming, and feature reviews—and collaborate with product managers, designers, and QA to deliver high\-quality features.
- Learn our cloud and deployment practices, including AWS, CI/CD pipelines, PostgreSQL, and Redis, and grow into owning your own components.
### Qualifications
Required* BS degree in Computer Science, Engineering, or a related field, or equivalent practical experience (bootcamp, self\-taught, or comparable).
- Solid programming fundamentals in at least one modern language (JavaScript/TypeScript, Python, Java, or similar), plus a working understanding of data structures, algorithms, and how web/API services work.
- A university project, capstone, internship project, or personal side project you can demonstrate and discuss in depth—ideally one that involves AI/LLMs (e.g., a chatbot, agent, RAG app, or an app built on an LLM API).
- Foundational understanding of generative AI / LLM concepts—prompting, tool/function calling, and the basics of how models are used in applications.
- Familiarity with relational databases (e.g., PostgreSQL) and basic SQL.
- Comfort with Git and collaborative development workflows.
- Strong written and verbal communication skills, and genuine eagerness to learn and take feedback.
Highly Desirable / Nice to Have* Hands\-on experience—even in a school or side project—with an LLM provider API (e.g., Anthropic Claude, OpenAI) or an agent framework (e.g., LangChain/LangGraph).
- Exposure to MCP (Model Context Protocol) servers or building tools/plugins that let an LLM call external functions.
- Any experience with Node.js/TypeScript, Express, or REST API development.
- Exposure to cloud platforms (especially AWS), Docker/containers, or CI/CD pipelines.
- Awareness of AI safety concerns—prompt injection, data leakage, hallucinations—and why guardrails matter.
- Interest in physical security, access control, or IoT.
- Prior internship or open\-source contributions.
### Why Work for Us?
Brivo is a Great Place to Work\-Certified™ company and the global leader in cloud\-based access control and video surveillance. Following our merger with Eagle Eye Networks, we are building the only platform powerful enough to support the future of AI\-driven security. Why Your Work Matters
Innovation drives our vibe, but purpose drives our mission. You will work on essential systems that protect the health, safety, and welfare of people and property worldwide. At Brivo, your voice is heard, your talent is respected, and your contributions have a global impact.* *The Brivo Experience:* We thrive on in\-person collaboration and a "one\-team" atmosphere. We embrace our international presence, leveraging diverse ideas and backgrounds to improve our culture and our products. To keep our global teams connected and inspired, we provide a premium onsite experience featuring communal meals, recurring social events, and fully stocked workspaces—ensuring you have everything you need to stay focused while building the future of security.
- *Total Rewards:* We support our people with competitive medical, vision, and dental plans (including company\-offset premiums), a 401k with company match, and an unlimited Paid Time Off (PTO) policy that empowers you to take the time you need to maintain a healthy work\-life balance.
Individual compensation packages are based on job\-related skills, experience, qualifications, work location, training, and market conditions. In addition, Brivonians enjoy a robust benefits and perks package tailored to their work location.### About Brivo
Brivo and Eagle Eye Networks have come together to create a category\-defining, cloud\-first platform at the intersection of AI and the physical world. Our mission is simple and ambitious: to make physical spaces safer, smarter, and more autonomous—from single\-site businesses to global enterprises.
As the unified global leaders in cloud\-based access control and video surveillance, we provide a comprehensive digital foundation for the built environment. By combining Brivo’s pioneering building access platform with Eagle Eye’s AI\-powered video management system (VMS), we have created a system of intelligence that protects over 600 million square feet across 90\+ countries. Every door, camera, and credential in our ecosystem acts as a real\-time sensor, leveraging AI to prevent incidents, improve operations, and enable entirely new workflows across sectors, including commercial real estate, retail, healthcare, education, and critical infrastructure.
With a global footprint spanning headquarters in Bethesda, Maryland, and Austin, Texas, and international offices in Amsterdam, London, Bangalore, and Tokyo, we are leveraging our open APIs and cyber\-secure cloud infrastructure to reshape the future of physical security. Join us as we build the world’s most robust platform for video intelligence and smart space automation. Learn more at www.brivo.com.
*Brivo is an equal employment opportunity employer and values diversity. Qualified candidates are considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, military or veteran status, disability, or any other characteristic protected by applicable law. If you require reasonable accommodations during the application or interview process, please inform us.*
Salary Context
This $120K-$144K 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 Brivo, 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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($132K) sits 40% below the category median. Disclosed range: $120K to $144K.
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.
Brivo AI Hiring
Brivo has 2 open AI roles right now. They're hiring across AI Software Engineer. Based in Bethesda, MD, US. Compensation range: $144K - $170K.
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
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