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About This Role
Position Purpose:
The Staff Software Engineer is responsible for leading a team of engineers building and designing a product that our customers and associates love. As a Staff Software Engineer, you will be part of a dynamic team with engineers of all experience levels who help each other build and grow technical and leadership skills while creating, deploying, and supporting production applications. In addition, Staff Software Engineers will assist in product and tool selection, configuration, security, resilience, performance tuning and production monitoring.
Staff Software Engineers contribute to foundational code elements that can be reused as well as architectural diagrams and other product\-related documentation.
As a Staff Software Engineer, you will be a core player on the product team and are expected to build and grow the skillsets of the more junior Engineers.
Key Responsibilities:
50% Delivery and Execution \- Develops, tests, deploys, and maintains software, with a clear understanding of the value the software is to provide; Takes a broad view when approaching issues; using a global lens; Consistently achieves results, even under tough circumstances; Develops test suites (functional, destructive, etc) to enable success, rapid deployment of code to production; Takes on new opportunities and tough challenges with a sense of urgency, high energy and enthusiasm; Consistently achieves results, even under tough circumstances
10% Learns and Grows \- Actively seeks ways to grow and be challenged using both formal and informal development channels; Learns through successful and failed experiment when tackling new problems
20% Plans and Aligns \- Creates new and better ways for the organization to be successful; Delivers multi\-mode communications that convey a clear understanding of the unique needs of different audiences; Works the Product Team to ensure user stories are developer ready, easy to understand and testable; Collaborates with other team members in agile processes; Relates openly and comfortably with diverse groups of people; Adapts approach and demeanor in real time to match the shifting demands of different situations
20% Supports and Enables \- Fields questions from product and engineering teams; Helps grow junior engineers by providing guidance on modern software development frameworks, and leading technical discussions; Notes gaps on the team and provides suggestions for changes to make the team more productive
Direct Manager/Direct Reports:
This position typically reports to Software Engineer Manager or Sr. Manager
This position typically has 0 Direct Reports
Travel Requirements:
No travel required.
Physical Requirements:
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.
Working Conditions:
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
Minimum Qualifications:
Must be eighteen years of age or older.
Must be legally permitted to work in the United States.
Preferred Qualifications:
Experience working with AI\-assisted development tools (e.g., GitHub Copilot, Claude Code, or similar coding agents) and the ability to evaluate output quality, not just generate it
Experience authoring or maintaining agent instruction layers, repo\-level AI context files, or equivalent intent artifacts that shape AI behavior at the codebase level
Experience mentoring engineers on responsible AI tool usage, including recognizing the limits of AI\-generated code
Experience with security frameworks for user and services authorization and authentication
Experience with creating and executing unit, functional, destructive and performance tests
Experience with modern debugging and root cause analysis techniques
Experience with version control system
Experience in designing systems for High Availability, Disaster Recovery, Performance, Efficiency, and Security
Exposure to developing technical roadmaps including work estimation, refactoring and modernizing legacy systems
Minimum Education:
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.
Preferred Education:
No additional education
Preferred Years of Work Experience:
No additional years of experience
Minimum Leadership Experience:
None
Preferred Leadership Experience:
None
Certifications:
None
Competencies:
Global Perspective
Manages Ambiguity
Nimble Learning
Self\-Development
Collaborates
Cultivates Innovation
Situational Adaptability
Communicates Effectively
Drives Results
Interpersonal Savvy
Salary Context
This $120K-$190K 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 The Home Depot, 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 ($155K) sits 29% below the category median. Disclosed range: $120K to $190K.
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.
The Home Depot AI Hiring
The Home Depot has 4 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Atlanta, GA, US, Denver, CO, US. Compensation range: $170K - $190K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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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