Full Stack AI Engineer

About the Role 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. Key Responsibilities 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. Preferred Qualifications 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. 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. 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). Role Scope Primarily a hands‑on technical leadership role. 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. Additional Requirements Periodic travel may be 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. Minimum qualifications: 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. Equal Opportunity Statement KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. #J-18808-Ljbffr