Silicon & Data Automation Systems Software Engineer, Staff

Overview

Senior individual contributor role building production-grade automation, data pipelines, database-backed applications, and engineering tools that improve silicon and system yield engineering workflows in the Bangalore Design Center, working closely with U.S.-based yield automation leadership.

What you'll do

• Design, develop, test, and maintain automation tools that improve silicon and system yield engineering workflows, including data processing, diagnostics, reporting, and operational efficiency.
• Build reliable Linux-based automation services, scripts, data loaders, and backend systems used by engineering teams.
• Develop production-grade solutions with appropriate logging, monitoring, error handling, alerting, documentation, and operational supportability.
• Debug and resolve automation issues across Linux servers, databases, file systems, scheduled jobs, data feeds, and dependent engineering systems.
• Build and maintain data pipelines that collect, transform, validate, and load engineering and manufacturing data across design, DFT, validation, diagnostics, and yield-related systems.
• Work with relational databases, SQL, schema design, query optimization, and database-backed automation workflows.
• Integrate data from multiple sources, including engineering systems, manufacturing data feeds, logs, reports, and analysis outputs.
• Use LLM-based coding agents and AI-assisted automation tools responsibly as part of day-to-day engineering work, maintaining strong human review of AI-generated code, SQL, analysis, documentation, and operational recommendations.
• Build or integrate AI-enabled engineering tools where appropriate, including automation agents, internal assistants, MCP servers, and workflow accelerators.
• Build backend tools, dashboards, web applications, APIs, command-line utilities, and scheduled automation to support engineering needs.
• Integrate automation into existing engineering workflows without disrupting production operations.
• Collaborate with engineers across design, DFT, validation, diagnostics, and data domains to convert manual pain points into reliable automated solutions.
• Participate in code reviews, design discussions, troubleshooting sessions, and production readiness reviews.

What you'll need

• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.
• OR Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
• OR PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Engineering, Software Engineering, or related field, or equivalent practical experience.
• Strong hands-on experience with Linux-based development and automation, including shell scripting, server-side troubleshooting, cron or scheduled jobs, file systems, permissions, and operational debugging.
• Strong programming skills in Python or a comparable language used for automation, data processing, backend systems, or engineering tools.
• Strong experience with SQL, relational databases, data modeling, query development, and database-backed applications.
• Experience building automation that processes, validates, transforms, or integrates large technical datasets.
• Experience developing production-quality software or automation with testing, logging, error handling, documentation, and maintainability.
• Experience using Git or similar version control systems in a collaborative environment.
• Practical experience using LLM-based coding agents or AI-assisted development tools to improve productivity.
• Ability to review AI-generated work critically and maintain ownership of correctness, security, reliability, and production readiness.
• Strong debugging and problem-solving skills across software, data, database, and Linux environments.
• Excellent written and verbal communication skills in English.
• Ability to work effectively with U.S.-based stakeholders with required time overlap.

Nice to have

• Experience with semiconductor design, DFT, validation, diagnostics, yield, or product engineering environments.
• Experience working with engineering datasets such as test data, DFT outputs, manufacturing data, diagnostic data, or high-volume silicon or system telemetry.
• Familiarity with semiconductor data formats such as STDF, KLARF, wafer maps, lot history, test results, binning, dispositions, or assembly data.
• Experience building automation for engineering teams in semiconductor, manufacturing, hardware, or similar domains.
• Experience with Oracle, PL/SQL, ODBC, database loaders, schema design, or production database integration.
• Experience with Django or similar backend frameworks.
• Experience with REST APIs, internal tools, dashboards, reporting systems, or workflow applications.
• Experience with log analytics, monitoring, Splunk, or observability tools.
• Experience with batch compute, distributed jobs, LSF or grid environments, or multi-server automation.
• Experience building or integrating AI-assisted tools, internal agents, MCP servers, or RAG workflows.
• Familiarity with responsible AI-assisted development practices, including human-in-the-loop review and secure handling of generated outputs.
• Experience working across global teams and time zones.

Details

• Location: Bangalore, India (Bangalore Design Center).
• Regular overlap with U.S. Central Time morning hours.
• Candidates with strong software, data, or automation backgrounds from non-semiconductor domains will be considered if they demonstrate the ability to learn complex engineering workflows quickly.