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About This Role
How to apply: Please complete your application on our hiring platform at https://app.intervuze.com/interview/upload/2dcab9b2-a69b-4378-bb2c-bdaf971bca60?utm_source=indeed&utm_medium=web&utm_campaign=indeed_web
About us
Bake More Pies is a full-service digital agency in Tampa. We do branding, marketing, technology, video production through BMP Studio, and a fast-growing AI practice.
Our AI Division builds real software for real businesses. That means voice and chat agents that sit on client websites, reporting platforms that pull data from a dozen sources every month, document automation that reads thousands of invoices, and computer vision on cellular cameras in the field. We also sell our own SaaS product. The team is small, so the work you ship is the work clients use.
The role
We're hiring a full-stack engineer who can take a client's messy problem, turn it into a Laravel app with AI at its core, put it into production, and keep it running. You'll own several client systems at once, from the first architecture sketch to the monthly support call.
In your first six months you will likely:
- Take over a live property-marketing reporting platform that pulls from CRMs, analytics, call tracking, and listing sites, then emails branded PDF reports to more than 150 properties every month.
- Finish a computer vision system that reads fill levels from cellular cameras through FTP and alerts operations staff.
- Improve an invoice-matching pipeline that uses an LLM to read about 1,500 vendor invoices a month and match them to accounts.
- Add features to a production quoting tool for a hurricane-protection manufacturer.
- Clean up and extend an ERP and CRM built on our internal Laravel platform.
- Contribute to our voice and chat AI product, which runs on a real-time speech model through a Node.js WebSocket layer.
You'll work daily with AI coding agents, and we expect you to be good at directing them and better at checking what they produce.
What you'll do
- Build features in Laravel, Livewire, and Filament, starting from user stories with clear acceptance criteria.
- Integrate LLMs into production workflows: extraction, summaries, retrieval over a knowledge base, and real-time voice.
- Connect outside systems through REST APIs, OAuth, webhooks, FTP, and scrapers for sites that have no API.
- Deploy and operate apps on Laravel Cloud and Forge, including queues, scheduled jobs, workers, DNS, and mail.
- Write tests first for bug fixes, and keep the suite green before every merge.
- Review AI-generated code with care, and use automated review tools as a second check, not the only one.
- Give written estimates before you start, track your time daily, and flag overruns the same day.
- Keep docs current: a README, a runbook, and a short status note on every open task.
- Handle secrets and client data safely: keys in environment config, least-privilege access, and rotation when something leaks.
- Demo work to clients, run QA sessions with them, and explain technical tradeoffs in plain language.
- Join our daily scrum and help shape architecture with the VP of AI.
What you need
- 3+ years building and shipping PHP applications in production, with at least 2 years on Laravel (version 10 or later).
- Hands-on work with Livewire or Filament, plus Tailwind and Alpine.js.
- At least one shipped feature that calls a hosted LLM API (OpenAI, Anthropic, Google Gemini, or similar), with error handling, retries, and cost controls.
- Solid MySQL skills: schema design, migrations, and data backfills you can verify.
- Experience with queues and scheduled jobs (Redis, Horizon, or similar).
- Comfort with OAuth, webhooks, and third-party APIs, including ones with poor documentation.
- A testing habit with PHPUnit or Pest.
- Experience deploying and debugging a Laravel app on your own (Laravel Cloud, Forge, or a VPS).
- Daily use of AI coding tools such as Claude Code, Cursor, or Codex, and a clear method for reviewing their output.
- Clear written and spoken communication with non-technical clients.
- Ability to work in our Tampa office on hybrid days.
Nice to have
- Node.js and WebSockets, especially real-time audio or streaming APIs.
- Python, OCR, or computer vision experience.
- Retrieval-augmented generation and vector search (Postgres with pgvector, or a hosted file search).
- Experience with business systems such as QuickBooks Online, a CRM, Airtable, or a contact center platform.
- Web scraping that holds up against JavaScript-heavy sites and logins.
- IoT, cellular devices, or 3D CAD for simple hardware enclosures.
- Agency or consulting background with several clients at once.
- Interest in leading client AI audits and discovery sessions.
Hiring process
A 30-minute phone screen, a 60-minute technical conversation, a short paid exercise, and a client demo role-play. We aim to make a decision within three weeks of your first call.
When you apply, include a short note about an AI feature you shipped: what it did, what broke, and how you fixed it. Links to code or a live demo help.
Bake More Pies is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other protected status.
Pay: $60,000.00 - $80,000.00 per year
Work Location: Hybrid remote in Tampa, FL 33607
Salary Context
This $60K-$80K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $193K across 172 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 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Bake More Pies, 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 $220,000 based on 1,448 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($70K) sits 68% below the category median. Disclosed range: $60K to $80K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Bake More Pies AI Hiring
Bake More Pies has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Tampa, FL, US. Compensation range: $80K - $80K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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