Software Engineering Manager – Remote Services

KLA•Ann Arbor, MI

1d•$153,300 - $260,600•Remote

About The Position

KLA Services is seeking a hands-on, AI-first Engineering Manager to lead the team building remote service software products for our field engineers who support and maintain KLA tools in the semiconductor fabrication plant, or "fab". This is a player-coach role: you will grow and lead a high-performing full-stack team while staying in the codebase yourself, setting the standard for how AI coding assistants and agentic workflows are used to design, build, and ship software. You will own the delivery, quality, and security of the remote service platform, ensuring our products remain robust, secure, and user-friendly and enabling seamless connectivity for our global workforce.

Requirements

Bachelor’s Degree or higher in related field or equivalent combination of any relevant education and experience.
8+ years of relevant experience with proven track record to lead including 4+ years of management experience.
8+ years of full-stack software engineering experience, with recent hands-on coding experience.
3+ years of experience leading or managing software engineering teams while remaining technically hands-on.

Nice To Haves

Proven track record of hiring, developing, and retaining engineering talent in a hands-on, high-ownership team culture.
Strong communication skills, with the ability to influence and work effectively with cross-functional teams and senior stakeholders.
Skilled at distilling ambiguous business problems into requirements, designs, and executable plans.
Experience delivering cloud native applications using Docker and Kubernetes.
Familiarity with modern web technologies such as HTML, CSS, JavaScript, Angular, and React.
Understanding of remote access protocols, VPNs, and security best practices.
Experience leading teams that practice Agile, Clean Code, and XP software development methods.
Demonstrated success using artificial intelligence to accelerate software engineering delivery, both individually and by raising the capability of an entire team.
Experience defining engineering standards for AI-assisted development, including prompt and context practices, code review of AI-generated changes, and security review.
Bachelor's degree in Computer Science, Information Technology, or a related field.

Responsibilities

Lead, coach, and grow a team of full-stack software engineers, including hiring, onboarding, performance feedback, and career development, while remaining an active technical contributor to the team's work.
Set technical direction for front-end applications, back-end services, APIs, and microservices, and stay hands-on through design reviews, code reviews, prototypes, and direct contributions to critical or ambiguous parts of the stack.
Partner with marketing, product management, IT infrastructure, security, and support to align engineering execution with business priorities.
Own roadmap development, backlog refinement, and release planning for the remote services portfolio.
Manage team capacity, sprint commitments, and dependencies so that milestones are delivered predictably.
Establish and uphold engineering standards for automated testing, CI/CD pipelines, observability, and production readiness.
Drive incident response and root-cause resolution for production issues across the full technology stack.
Ensure compliance with relevant regulations and standards, and maintain the integrity and security of remote access systems.
Lead an AI-first engineering practice: use coding assistants such as Claude Code and Devin in your own daily work, and define the standards, guardrails, and review practices that make AI-accelerated delivery safe, secure, and effective across the team.
Personally evaluate emerging AI engineering tools, agentic workflows, and remote access technologies, run pilots with the team, and decide where to invest based on measured results.
Manage stakeholder communication, including status reporting, risk escalation, and budget or vendor discussions as needed.
Stay hands-on by writing and reviewing code, building prototypes, and pairing with engineers on complex problems, dedicating a meaningful share of your time to technical work.
Model AI-first engineering behavior day to day, sharing working patterns, measuring their impact on cycle time and quality, and coaching engineers to adopt what works.