KLA
Specialist, Technology - Software
India · Work style not stated · Full time
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About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerKLA
- LocationIndia
- Work styleWork style not stated
- Employment typeFull time
- Employer posted
To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale—faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology.
Group/Division
The Semiconductor Products and Customers (Semi PC) business unit designs, builds and sells KLA’s product portfolio to help chip manufacturers meet high-quality standards for technologies like AI, data centers, automotive and electronic devices. Our inspection, metrology, and analytics systems detect and monitor defects across logic and memory chips, specialty semiconductors, wafers, reticles, advanced packaging, process equipment and materials. We also develop technologies for specialty processes, IC substrates, and PCB manufacturing, including etch and deposition, component inspection, and imaging and analytics. The LS-SWIFT division delivers high-throughput patterned wafer inspection systems that support advanced semiconductor manufacturing. Its mission is to provide industry-leading defect detection with optimal cost of ownership across a wide range of applications. LS systems enable precise, cost-effective inspection for cutting-edge process nodes, while SWIFT systems offer comprehensive macro inspection of all wafer surfaces—capabilities that are especially critical for advanced packaging, as well as logic, memory, and automotive applications.
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What You'll Do
In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise.
Key Responsibilities:
Strong software architecture expertise designing complex, distributed, scalable, high-performance, and data-intensive systems.
Experience across legacy and modern technology stacks, with the ability to evolve existing platforms and drive architectural improvements.
Deep technical knowledge in one or more areas: enterprise architecture, cloud-native services, microservices, AI/ML infrastructure, big data platforms, or DevOps automation.
Proven ability to design and deliver medium-to-large scale software systems in multi-developer, cross-functional environments.
Strong systems thinking and analytical skills, capable of simplifying ambiguity, evaluating trade-offs, and solving complex technical challenges.
Expertise in scalability, performance optimization, reliability, and future-proof software design, ensuring robust architectures, code quality, and maintainability.
Ability to translate complex business and technical requirements into architecture, detailed designs, and executable engineering plans.
Strong technical leadership and mentoring skills, influencing architects, senior engineers, and technical leads across organizations, geographies, and disciplines.
Excellent communication and collaboration skills, effectively engaging both technical and non-technical stakeholders in global teams.
Ownership-driven mindset with a focus on execution, innovation, and engineering excellence, leveraging modern development practices and AI-assisted engineering tools.
Preferred Qualifications:
Experience building and architecting complex distributed systems.
Familiarity with UI/UX design considerations in engineering applications.
Technical Skills:
Programming: C#, C++, Java, Python, .NET
Architectural Paradigms: Microservices, service-oriented architecture, modular monolith, layered architecture, event-driven architecture
Legacy Modernization: Monolith decomposition, migration from thick-client/desktop stacks to modern service-based platforms, backend/frontend separationWorking knowledge of container technologies, orchestration frameworks (e.g., Kubernetes), and workflow automation.Strong grasp of software development best practices, CI/CD, and DevOps principles.
Leadership & Communication: Demonstrated ability to lead and drive functional teams. Excellent communication and stakeholder management skills. Passion for mentoring and developing engineering talent.
Minimum Qualifications
Doctorate (Academic) Degree and related work experience of 3 years; Master's Level Degree and related work experience of 6 years; Bachelor's Level Degree and related work experience of 8 years
About KLA
We provide advanced inspection tools, metrology systems, process solutions, and computational analytics that make electronics possible, tackling complex challenges. From electron and photon optics to machine learning and data analytics, we seek perfection at the most fundamental level of matter in the universe. If you want to make electronics that push industries forward and make the world a better place, join us.
Use of AI Statement
At KLA, our interviews seek to understand your individual skills, problem-solving approach and authentic thinking. To ensure a fair and consistent evaluation, the use of AI, recording tools or other technologies to generate, suggest or provide responses during interviews—whether virtual or in person—is not permitted unless explicitly approved in advance as part of a reasonable accommodation or invited by the interviewer. Use of these tools may interfere with our ability to evaluate your individual qualifications and affect your candidacy. KLA is committed to advancing innovation through responsible AI, and we value candidates who share this mindset.
We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.
KLA is proud to be an equal opportunity employer.
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At a glance
- Employment typeFull time
- Employer posted
- Added to ROLIVA
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Skills in this posting
Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.
Python Kubernetes Java Machine learning Stakeholder management