{"id":2724488,"url":"https://alion.io/job/qualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield","title":"Staff Engineer, Silicon & Data Automation Systems (Design, DFT, Diagnostics, Yield)","company":{"id":94,"name":"Qualcomm","domain":"qualcomm.com","url":"https://alion.io/company/qualcomm","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":71,"open_postings":1151,"ghost_share":0.235,"stale_share":0.133,"repost_share":0.467,"time_to_fill_p50_days":74,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":98000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":25},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Django","optional":true},{"name":"Git","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Oracle","optional":true},{"name":"Python","optional":true},{"name":"RAG","optional":true},{"name":"Rest API","optional":true},{"name":"Rest-Assured","optional":true},{"name":"Splunk","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-06-28T00:00:00Z","employer_posted_date":"2026-06-28","last_verified_at":"2026-10-23T00:34:21Z","board_verified":true,"closed_at":null,"days_open":117,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":117},"description":"Company:\nQualcomm India Private LimitedJob Area:\nEngineering Group, Engineering Group > Hardware EngineeringGeneral Summary:\nWe are seeking a highly motivated and technically strong Staff Engineer, Silicon & Data Automation Systems to help build and expand a growing automation team supporting silicon and system yield engineering, spanning design, DFT, diagnostics, and yield engineering workflows. This role will focus on developing production-grade automation, data pipelines, database-backed applications, and engineering tools that improve the speed, quality, and scalability of complex semiconductor engineering workflows.\nThis position is part of a broader effort to increase automation capacity within the silicon engineering organization, beginning with new engineering roles in the Bangalore Design Center (BDC). The engineer will work closely with U.S.-based yield automation leadership and stakeholders, including regular overlap with U.S. Central Time morning hours.\nThis is asenior individual contributor role. The successful candidate will build new automation capabilities under architectural guidance, contribute to robust production systems, and use modern AI-assisted engineering practices to increase development velocity and quality. This role requires anAI-first engineering mindset, where LLM-based coding agents and AI-assisted automation tools are used as core productivity multipliers while maintaining strong human ownership of correctness, security, review, and production safety.\nThe ideal candidate is a strong Linux, data, database, and automation engineer who can work effectively in complex semiconductor engineering environments. Prior experience with semiconductor engineering domains such as silicon design, DFT, validation, diagnostics, or yield is strongly preferred but not required for candidates with strong automation and data engineering depth.\nMinimum Qualifications:\n• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.OR\nMaster's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.\nOR\nPhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.\nKey Responsibilities\nAutomation Development & Production Engineering\nDesign, develop, test, and maintain automation tools that improve silicon and system yield engineering workflows, including data processing, diagnostics, reporting, and operation efficiency.\n\nBuild reliable Linux-based automation services, scripts, data loaders, and backend systems used by engineering teams.\n\nDevelop production-grade solutions with appropriate logging, monitoring, error handling, alerting, documentation, and operational supportability.\n\nContribute to systems that are maintainable, fault-tolerant, secure, and suitable for long-running production use.\n\nDebug and resolve automation issues across Linux servers, databases, file systems, scheduled jobs, data feeds, and dependent engineering systems.\n\nWork under architectural guidance to implement new automation capabilities while developing deeper ownership of specific tools, workflows, or data domains over time.\n\nData Systems & Database Automation\nBuild and maintain data pipelines that collect, transform, validate, and load engineering and manufacturing data across design, DFT, validation, diagnostics, and yield-related systems.\n\nWork with relational databases, SQL, schema design, query optimization, and database-backed automation workflows.\n\nIntegrate data from multiple sources, including engineering systems, manufacturing data feeds, logs, reports, and analysis outputs.\n\nDevelop tools that make complex data easier to access, validate, monitor, and act upon.\n\nEnsure data quality, traceability, and operational robustness in automation that supports engineering analysis and decision-making.\n\nAI-Assisted Engineering & Automation Acceleration\nUse LLM-based coding agents and AI-assisted automation tools responsibly as part of day-to-day engineering work.\n\nApply AI-assisted development practices to improve code quality, accelerate troubleshooting, generate tests, improve documentation, and increase engineering output.\n\nBuild or integrate AI-enabled engineering tools where appropriate, including automation agents, internal assistants, MCP servers, and workflow accelerators.\n\nMaintain strong human review and engineering judgment for AI-generated code, SQL, analysis, documentation, and operational recommendations.\n\nEnsure AI-assisted workflows follow appropriate standards for security, correctness, maintainability, and production safety.\n\nHelp establish practical patterns for using AI-first development methods in production engineering environments.\n\nTooling, Applications & Workflow Integration\nBuild backend tools, dashboards, web applications, APIs, command-line utilities, and scheduled automation to support engineering needs.\n\nUse appropriate technologies for the problem, including Python, shell scripting, SQL, Django or similar frameworks, REST APIs, log analytics tools, and enterprise data systems.\n\nIntegrate automation into existing engineering workflows without disrupting production operations.\n\nCollaborate with engineers and stakeholders to identify manual pain points and convert them into reliable automated solutions.\n\nCreate clear documentation, usage guidance, and operational notes so tools can be supported and extended over time.\n\nCross-Functional Collaboration\nWork closely with engineers across design, DFT, validation, diagnostics, and data domains to understand requirements and deliver practical solutions.\n\nCommunicate technical findings, implementation options, risks, and tradeoffs clearly to both software-oriented and semiconductor engineering audiences.\n\nParticipate in code reviews, design discussions, troubleshooting sessions, and production readiness reviews.\n\nCollaborate effectively across time zones, including regular overlap with U.S. Central Time morning hours.\n\nContribute to a growing team culture focused on engineering rigor, accountability, automation leverage, and continuous improvement.\n\nRequired Qualifications\nBachelor’s orMaster’s degree in Computer Science, Electrical Engineering, Data Engineering, Software Engineering, or related field, or equivalent practical experience.\n\nStrong hands-on experience with Linux-based development and automation, including shell scripting, server-side troubleshooting,cronor scheduled jobs, file systems, permissions, and operational debugging.\n\nStrong programming skills in Python or a comparable language used for automation, data processing, backend systems, or engineering tools.\n\nStrong experience with SQL, relational databases, data modeling, query development, and database-backed applications.\n\nExperience building automation that processes, validates, transforms, or integrates large technical datasets.\n\nExperience developing production-quality software or automation with testing, logging, error handling, documentation, and maintainability.\n\nExperience using Git or similar version control systems in a collaborative environment.\n\nPractical experience using LLM-based coding agents or AI-assisted development tools to improve productivity.\n\nAbility to review AI-generated work critically and maintain ownership of correctness, security, reliability, and production readiness.\n\nStrong debugging and problem-solving skills across software, data, database, and Linux environments.\n\nExcellent written and verbal communication skills in English.\n\nAbility to work effectively with U.S.-based stakeholders with required time overlap.\n\nAdditional consideration:\nCandidates 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.\n\nPreferred Qualifications\nExperience with semiconductor design, DFT, validation, diagnostics, yield, or product engineering environments.\n\nExperience working with engineering datasets such as test data, DFT outputs, manufacturing data, diagnostic data, or high-volume silicon or system telemetry.\n\nFamiliarity with semiconductor data formats such as STDF, KLARF, wafer maps, lot history, test results, binning, dispositions, or assembly data.\n\nExperience building automation for engineering teams in semiconductor, manufacturing, hardware, or similar domains.\n\nExperience with Oracle, PL/SQL, ODBC, database loaders, schema design, or production database integration.\n\nExperience with Django or similar backend frameworks.\n\nExperience with REST APIs, internal tools, dashboards, reporting systems, or workflow applications.\n\nExperience with log analytics, monitoring, Splunk, or observability tools.\n\nExperience with batch compute, distributed jobs, LSF or grid environments, or multi-server automation.\n\nExperience building or integrating AI-assisted tools, internal agents, MCP servers, or RAG workflows.\n\nFamiliarity with responsible AI-assisted development practices, including human-in-the-loop review and secure handling of generated outputs.\n\nExperience working across global teams and time zones.\n\nDesired Technical Profile\nThe ideal candidate operates across multiple layers of the engineering stack:\nLinux: Comfortable diagnosing runtime issues, managing scripts, and troubleshooting production systems.\n\nData: Able to handle complex, messy engineering data and build reliable transformations with traceability.\n\nDatabases: Strong SQL skills with practical understanding of schemas, performance, and data integrity.\n\nAutomation: Able to convert manual workflows into robust and scalable systems.\n\nProduction Mindset: Builds systems that are observable, maintainable, secure, and resilient.\n\nAI-First Engineering: Uses AI tools to increase output while maintaining full accountability.\n\nEngineering Communication: Works effectively with domain experts and delivers practical solutions.\n\nWhat Success Looks Like\nA successful engineer in this role will:\nDeliver reliable automation that reduces manual effort for silicon and systems yield engineering teams across design, DFT, diagnostics, and yield workflows.\n\nBuild data tools and pipelines that engineers trust and reuse.\n\nImprove development velocity and quality through responsible use of AI-assisted tools.\n\nContribute production-ready systems that scale across teams and time zones.\n\nLearn semiconductor workflows well enough to translate engineering needs into practical solutions.\n\nOperate as a strong senior individual contributor while growing into deeper ownership.\n\nHelp establish the foundation for a larger Bangalore-based automation capability.\n\nApplicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail  or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).\nQualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.\nTo all Staffing and Recruiti...","description_format":"text","description_chars":12646,"description_truncated":true,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Autonomous Driving","RF & Wireless Hardware","Car Electronics"],"lifecycle":[{"event":"open","at":"2026-10-16T15:50:00Z"}],"visa":[],"liveness":{"score":27,"band":"fade","label":"Fading","p_open":1,"p_active":0.738,"p_room":0.36,"age_days":116,"expected_fill_days":74,"reasons":["conf:1","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/qualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield","json_url":"https://alion.io/job/qualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield.json","meta":{"generated_at":"2026-10-23T01:02:12Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":1738,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-24T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":94},"rest":"https://alion.io/mcp/rest/get_company?id=94"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fqualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fqualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fqualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/qualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fqualcomm-staff-engineer-silicon-data-automation-systems-design-dft-diagnostics-yield"}]}