Senior AI Software Engineer

Port Saint Lucie, FL, US Senior AI Software Engineer

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Skills & Technologies

ClaudeN8NPythonTypescript

About This Role

AI job market dashboard showing open roles by category

EZETech is hiring a senior engineer who builds with AI every day and can still read, defend, and secure every line that ships. You will take our internal security and compliance platforms from single-builder projects to multi-tenant SaaS that regulated clients can trust. About EZETech EZETech is a managed security service provider on Florida's Treasure Coast. Our nine-person team secures roughly 600 endpoints for dental, medical, and financial clients, and we operate under HIPAA, SOC 2, PCI DSS, CMMC 2.0, and ISO 27001. We build our own tooling: our internal platforms cover compliance automation, vulnerability and exposure management, endpoint application control, and service operations, and we are building a combined CRM and EHR for behavioral health clinics. The next step is selling these platforms to other providers as SaaS. Today they are built largely by our founder using AI coding agents. This role adds the engineering depth that turns working software into products that survive audits, attackers, and paying tenants. What you will build and own (reporting directly to the founder) - Product engineering: multi-tenant SaaS features across our security and compliance platforms, front end to database - AI-assisted delivery with accountability: use coding agents such as Claude Code, then review, test, and own the output. If you cannot explain a change, it does not merge - Agent and LLM systems: agent workflows, tool integrations, and retrieval pipelines on hosted APIs and local inference, defended against prompt injection, data leakage, and excessive agent permissions - Security architecture: authentication, authorization, tenant isolation, secrets management, encryption, audit logging, and threat modeling - Infrastructure and networking: deployments, CI/CD, DNS, TLS, reverse proxies, private mesh networking, firewalls, backups, and tested restores - Regulated data handling: systems for protected health information with controls that hold up in a HIPAA or SOC 2 audit - Hardening existing code and operational ownership: fix weak points in priority order, monitor what you ship, respond when it breaks, write the postmortem Required qualifications - 5+ years building production software, including at least one SaaS product you helped ship and then operate - Strong in TypeScript/Node, Python, or Go, plus a modern front-end framework such as React - Solid PostgreSQL (or equivalent) skills: schema design, migrations, indexing, row-level access control - Disciplined with Git, code review, automated tests, and CI/CD; able to find bugs and security flaws in unfamiliar and AI-generated code - Working knowledge of the OWASP Top 10; has correctly implemented OAuth 2.0/OIDC, SSO, MFA, session handling, and role-based access - Understands multi-tenant isolation, secrets, keys, and encryption in transit and at rest; thinks in least privilege, logging, and recoverability - Understands TCP/IP, DNS, TLS, HTTP, reverse proxies, VPNs, and firewall rules well enough to debug with a packet capture - Has run services on Linux with containers, designed backups, and performed a real restore - Daily, fluent user of AI coding agents with a clear verification process; has built with LLM APIs beyond a chat wrapper (tool use, agents, structured output, retrieval, or evaluation) and understands hallucination, prompt injection, and context limits - Authorized to work in the United States and able to pass a background check (you will access systems protecting patient and financial data) - Clear written communication: you document decisions, risks, and how to recover Preferred qualifications - Experience at an MSP, MSSP, or security software vendor - Built software under HIPAA, SOC 2, PCI DSS, CMMC, or ISO 27001, or answered the questions in an audit - Healthcare software experience: EHR or practice management, HL7 or FHIR - Endpoint/systems work: Windows internals, agents and services, Active Directory, PowerShell - Local model inference (Ollama or similar), GPU hosts, and workflow automation such as n8n - Offensive security exposure: penetration testing, CTFs, bug bounty, or OSINT tooling - Security certifications are welcome but do not replace shipped work Who this role is not for - You prompt until it runs and ship it without reading the diff - You cannot explain how your last project handled authentication, tenant separation, or secrets - You treat security and compliance as someone else's job or a final checklist - You want a large team, a narrow lane, and a product manager writing your tickets. We are nine people and you will own outcomes end to end How we hire 1. Application: resume plus links to code or products you built. Tell us which parts you wrote, which parts an AI wrote, and how you verified the AI's work 2. Technical conversation (45 minutes): walk us through a system you built 3. Paid work sample (about 3 hours): review a small AI-generated application with planted security and networking flaws, report findings in priority order, and fix the top issues. AI tools are allowed and expected 4. Founder interview 5. References and background check How to apply Use our resume form at https://ezetech.com/submit-resume/ (full details at https://ezetech.com/jobs/senior-ai-software-engineer/). In its Message box, name this role and include the links and notes described in step 1 above. You can also apply here on Indeed, but please still send the step 1 links and notes. EZETech is an equal opportunity company and welcomes applicants of all backgrounds.

People with a criminal record are encouraged to apply

Work Location: In person

Role Details

Company EZETECH LLC
Title Senior AI Software Engineer
Location Port Saint Lucie, FL, US
Category AI Software Engineer
Experience Senior
Salary Not disclosed
Remote No

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 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At EZETECH LLC, 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

Claude (5% of roles) N8N Python (18% of roles) Typescript (3% of roles)

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 $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

EZETECH LLC AI Hiring

EZETECH LLC has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Port Saint Lucie, FL, US.

Location Context

Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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

Based on 1,601 roles with disclosed compensation, the median salary for AI Software Engineer positions is $220,000. Actual compensation varies by seniority, location, and company stage.
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.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
EZETECH LLC is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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