Interested in this AI Software Engineer role at Brivo?
Apply Now →Skills & Technologies
About This Role
### Description
As a key technical leader, you will own the architecture and delivery of the high\-availability, low\-latency AI platform that powers intelligent capabilities across Brivo's core access control and video products. This requires a proactive approach to system ownership—not only implementing features but also defining the technical roadmap for LLM orchestration, tooling, and agent infrastructure, driving architectural discussions on AI safety and reliability, and providing technical guidance to the team. You will directly own the underlying services, integrations, streaming pipelines, and guardrail systems that make generative AI safe and dependable in production. Our best engineers are adept at picking up new things, enjoy solving challenging problems, speak up, and thrive in a dynamic and fast\-paced environment.
You will join a high\-impact team dedicated to building the next generation of AI\-powered experiences on Brivo's platform. This team helps Brivo customers derive value from their access control and video systems by making buildings and their data intelligible and actionable through AI—developing platform capabilities ranging from multi\-agent orchestration and LLM safety guardrails to tool/MCP servers, real\-time streaming, and deep platform integrations.### Responsibilities
- Design, build, and operate MCP (Model Context Protocol) servers and tool registries that expose platform capabilities to LLMs and agents safely and reliably.
- Deliver generative AI capabilities across the platform—prompt engineering, tool/function calling, agent routing, and stateful human\-in\-the\-loop workflows—that are safe, responsive, and cost\-efficient.
- Build and maintain AI safety guardrails (prompt\-injection, data\-exposure, and relevance/abuse detection) and resumable tool workflows using Redis\-backed checkpointing.
- Spend approximately 70% of your time coding. This includes architecting and developing scalable, production\-grade API and platform services primarily utilizing Node.js/TypeScript and Express for containerized and serverless (AWS Lambda) delivery, backed by an LLM\-driven multi\-agent orchestration framework.
- Drive technical design, document key decisions (e.g., Architecture Decision Records \- ADRs), and participate rigorously in code reviews and design sessions to maintain the highest quality engineering standards.
- Own the cloud infrastructure and deployment pipelines, utilizing AWS (Lambda, SQS, Secrets Manager, SSM), CI/CD tooling, feature flags (LaunchDarkly), and externalized configuration (Spring Cloud Config) to automate provisioning and ensure continuous integration and delivery.
- Collaborate effectively with product managers and designers to design and deliver high\-quality features. Work within an Agile team to complete sprint planning, backlog grooming, feature reviews, and closely support your Team Lead with project scoping.
- Troubleshoot and resolve complex, high\-impact production issues, taking full responsibility for application ownership. Proactively identify security vulnerabilities, harden service\-to\-service auth and rate limiting, and optimize database performance and data models within PostgreSQL.
- Set a high bar for engineering excellence and serve as a technical mentor to team members, driving process improvements and promoting best practices across the engineering department.
- Partner with other teams across the organization to support the company's mission through architectural and technical improvements.
### Qualifications
Required* 5\+ years of professional experience designing, developing, and deploying highly available, scalable software solutions.
- 5\+ years of deep, hands\-on experience with Node.js and TypeScript, including serverless development on AWS Lambda.
- Direct experience building and operating MCP servers (or comparable LLM tool/plugin servers) in production.
- Proven experience building production REST API services with Express (or equivalent), including authentication, rate limiting, input validation, and OpenAPI/Swagger documentation.
- Hands\-on experience developing LLM\-enabled / generative AI applications—tool calling, multi\-agent orchestration, and prompt engineering.
- Strong experience with AWS, containerized deployments, and CI/CD tools.
- Deep practical experience with relational databases, specifically PostgreSQL, and query optimization.
- Experience with real\-time streaming (Server\-Sent Events and/or message queues such as AWS SQS) and Redis for state management.
- BS degree in Computer Science, Engineering, or a related field, or equivalent practical experience. An advanced degree is preferred.
- Exceptional written and verbal communication skills, with the ability to articulate complex technical concepts to both technical and non\-technical stakeholders.
Highly Desirable Skills* Direct experience developing AI\-enabled services, familiarity with LLM provider APIs (e.g., Anthropic Claude, OpenAI), and advanced context/prompt engineering techniques.
- Experience designing AI safety guardrails (prompt\-injection defense, data\-exposure prevention) and human\-in\-the\-loop confirmation flows for sensitive operations.
- Experience authoring and scaling MCP server ecosystems—tool/resource design, transport, and access control for agent\-facing APIs.
- Experience with schema\-validation libraries (e.g., Zod), feature\-flagging platforms (LaunchDarkly), and externalized configuration (Spring Cloud Config).
- Familiarity with agent\-orchestration frameworks (e.g., LangChain/LangGraph or equivalent) and LLM evaluation, tracing, and cost/latency optimization.
- Deep expertise in authentication and authorization, including OAuth 2\.0, OIDC, and role\-based access control for secure, multi\-tenant enterprise platforms.
- Domain experience in physical security, access control, or IoT platforms.
### 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 $150K-$170K 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 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($160K) sits 27% below the category median. Disclosed range: $150K to $170K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.