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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack AI Engineer - **Company:** KLA Corporation - **Location:** Chandler, AZ, United States - **Experience:** Experienced - **Salary:** $111,900.0 - $190,200.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Application Layers, Distributed Systems, Machine Learning, Systems Integration, Software Technical Review, Large Language Models, Reliability of Systems, Generative AI, Information Technology, Machine Learning Operations, Data Pipelines, Automation Anywhere - **Published:** June 5, 2026 - **Apply:** https://diversityjobs.com/career/17140562/Full-Stack-Ai-Engineer-Arizona-Chandler ## About the Role Technical Expertise * 5-8 years of experience building production software systems * At least 2 years working with AI/ML or LLM-based solutions in production environments * Demonstrated ownership of delivering end-to-end AI systems or features * Strong understanding of modern AI development practices (e.g., evaluation, prompt iteration, system integration) * Comfortable working across the stack, including data pipelines, model serving, and application layers * Sound judgment in making technical trade-offs, including build vs. buy decisions AI / Applied Systems Experience * Hands-on experience with LLMs, agent-based systems, or generative AI applications * Familiarity with evaluation frameworks, prompt iteration, and model behavior tuning * Understanding of limitations and failure modes of AI systems, and how to design around them * Experience operationalizing AI workflows (e.g., pipelines, monitoring, feedback loops) in real-world environments Leadership & Mentorship * Experience serving as a technical lead or senior engineer on a team * Proven ability to mentor and uplift other engineers * Strong communication skills, including technical documentation and stakeholder engagement * Ability to influence decisions and drive alignment without formal authority * Interest in growing leadership scope over time (optional, not required), * Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, or a related technical field * Advanced degree (MS or PhD) preferred, particularly with a focus on AI, Machine Learning, or distributed systems, * Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years;OR equivalent work experience ## Description We are seeking an AI Engineer to serve as a technical lead within a growing, operations-aligned engineering team. This role is ideal for someone who combines strong hands-on engineering capability with a passion for mentoring others and shaping how teams build and scale AI systems. You will work alongside data scientists and full-stack engineers to deliver AI-powered solutions across internal tooling, customer-facing features, and the supporting data/ML infrastructure. The team is actively shipping; this role focuses on strengthening technical execution, improving system reliability, and elevating overall engineering practices. While there will be opportunities to take on broader leadership responsibilities over time, the primary focus of this role is technical leadership, delivery, and mentorship., * Lead the design, development, and deployment of production AI systems end-to-end * Contribute hands-on to the codebase and set a high bar for engineering quality * Establish scalable patterns for evaluation, deployment, and system reliability * Conduct technical design reviews and guide architectural decisions * Mentor and develop engineers, providing regular coaching and technical guidance * Support hiring efforts, including candidate evaluation and onboarding * Partner with cross-functional stakeholders to align priorities and deliver impactful solutions * Help translate experimentation into stable, production-ready systems, * Emphasis on delivery, system quality, and team enablement * Opportunities to expand into people leadership over time, based on interest and business needs * Not a research-focused role - emphasis is on applied, production systems ## Related Videos - [One AI API to Power Them All](https://www.wearedevelopers.com/videos/1601-one-ai-api-to-power-them-all) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)