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About This Role
Job Title: Lead GenAI Full Stack Engineer
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Location: Charlotte, NC
Employment Type: Contract (C2C)
Pay Rate: $70–$75/hr C2C (Lead Candidates)
Job Summary
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We are seeking a highly skilled Lead GenAI Full Stack Engineer to lead the enterprise\-wide rollout and adoption of Generative AI solutions across engineering teams. The ideal candidate will have strong full\-stack development expertise, hands\-on experience with modern GenAI tools, and a proven ability to integrate AI capabilities into enterprise software development workflows.
This is a hands\-on technical leadership role where you will drive AI\-powered developer productivity, implement enterprise AI solutions, and collaborate with cross\-functional teams to modernize the software development lifecycle.
Key Responsibilities
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- Lead the end\-to\-end implementation and enterprise rollout of Generative AI tools such as Devin, Claude Code, Cursor, GitHub Copilot, and similar developer productivity platforms.
- Design and implement scalable AI\-enabled development workflows across engineering teams.
- Develop and integrate enterprise applications using Java, Python, React/Angular, and TypeScript.
- Build and integrate AI capabilities into enterprise SDLC processes, including CI/CD pipelines, code repositories, APIs, and automation workflows.
- Define rollout strategies, implementation roadmaps, and onboarding plans for enterprise\-wide AI adoption.
- Partner with engineering and business teams to improve software delivery using Generative AI technologies.
- Conduct developer enablement sessions, technical workshops, and training on AI tools, prompt engineering, and best practices.
- Monitor adoption metrics, usage analytics, and platform performance while driving continuous improvement.
- Troubleshoot implementation challenges and optimize AI tool performance at scale.
- Develop reusable playbooks, standards, and governance models for enterprise AI adoption.
- Ensure compliance with enterprise security, governance, and regulatory standards.
- Collaborate with cross\-functional stakeholders to translate business requirements into scalable technical solutions.
Required Qualifications
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- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 10\+ years of software engineering experience with strong full\-stack development expertise.
- Proven experience leading enterprise software development initiatives.
- Hands\-on experience developing applications using:
+ Java
+ Python
+ React or Angular
+ TypeScript
- Strong experience with:
+ Distributed Systems
+ Microservices Architecture
+ Event\-Driven Architecture
+ REST API Development \& Integration
- Experience implementing and maintaining:
+ CI/CD Pipelines
+ Developer Tooling Ecosystems
- Experience with cloud platforms such as:
+ Google Cloud Platform (GCP)
+ OpenShift (OCP)
Required GenAI Skills
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- Hands\-on experience with enterprise Generative AI tools such as:
+ Devin
+ Claude / Anthropic Models
+ Cursor
+ GitHub Copilot or similar AI coding assistants
- Strong understanding of:
+ Prompt Engineering
+ Retrieval\-Augmented Generation (RAG)
+ Agent\-Based Workflows
+ Multi\-Agent Systems
+ Model Context Protocol (MCP)
+ AI Orchestration \& Tool Chaining
+ Autonomous Agentic Systems
Preferred Qualifications
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- Experience driving enterprise\-wide AI adoption initiatives.
- Experience working in regulated enterprise environments with governance and compliance requirements.
- Strong leadership and mentoring experience.
- Excellent communication and stakeholder management skills.
- Experience collaborating with cross\-functional engineering and business teams.
- Passion for emerging AI technologies and developer productivity improvements.
Required Technical Skills
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- Java
- Python
- React
- Angular
- TypeScript
- Microservices
- Distributed Systems
- Event\-Driven Architecture
- REST APIs
- CI/CD
- Git
- OpenShift (OCP)
- Google Cloud Platform (GCP)
- Devin
- Claude / Anthropic
- Cursor
- GitHub Copilot
- Prompt Engineering
- Retrieval\-Augmented Generation (RAG)
- Model Context Protocol (MCP)
- Agentic AI
- Multi\-Agent Systems
- AI Orchestration
- Developer Productivity Tools
Preferred Skills
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- Enterprise AI Platform Implementation
- Software Development Lifecycle (SDLC)
- DevOps
- Cloud\-Native Applications
- API Integration
- Enterprise Architecture
- Technical Leadership
- AI Governance
- Security \& Compliance
Why Join?
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- Work on cutting\-edge enterprise Generative AI initiatives.
- Lead AI transformation across large\-scale engineering organizations.
- Collaborate with highly skilled engineering teams on innovative AI solutions.
- Opportunity to shape the future of AI\-powered software development within a global enterprise.
Salary Context
This $145K-$156K 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 Vision Square Inc, 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 ($150K) sits 31% below the category median. Disclosed range: $145K to $156K.
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.
Vision Square Inc AI Hiring
Vision Square Inc has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Charlotte, NC, US. Compensation range: $156K - $156K.
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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