{"id":2911283,"url":"https://alion.io/job/amd-product-development-engineer-agentic-ai-analytics","title":"Product Development Engineer -Agentic AI & Analytics","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":77,"open_postings":170,"ghost_share":0,"stale_share":0.906,"repost_share":0,"time_to_fill_p50_days":32,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Hardware","role_family":"Hardware","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":43000,"max_usd":112000,"period":"year","method":"role_country_seniority_unknown","sample_n":97},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Rest API","optional":false},{"name":"AI Agents","optional":true},{"name":"AutoGen","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Confluence","optional":true},{"name":"Copilot","optional":true},{"name":"CrewAI","optional":true},{"name":"Databricks","optional":true},{"name":"Django","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"Function Calling","optional":true},{"name":"Git","optional":true},{"name":"Jira","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Linux","optional":true},{"name":"Matplotlib","optional":true},{"name":"Microsoft Teams","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"NLP","optional":true},{"name":"OpenAI SDK","optional":true},{"name":"Outlook","optional":true},{"name":"Plotly","optional":true},{"name":"Power BI","optional":true},{"name":"Python","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"SharePoint","optional":true},{"name":"Snowflake","optional":true},{"name":"SQL","optional":true},{"name":"Tableau","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-14T03:00:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-30T00:03:32Z","board_verified":true,"closed_at":null,"days_open":45,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":45},"description":"ADVANCE YOUR CAREER. ADVANCE THE WORLD.\nAt AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.\nWhether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger - technology that moves the world forward. Join us and, together, we’ll advance your career.\nTHE ROLE:\nWe are seeking a highly motivated engineer to develop software, data, automation, and AI-driven solutions that improve Product Engineering productivity and decision-making. You will build tools, analytics, dashboards, and intelligent applications that help engineering teams work more efficiently and gain insights from complex manufacturing and engineering data.\nTHE PERSON:\nYou are a hands-on problem solver with strong software and data skills, a passion for automation and AI, and the ability to turn ideas into practical solutions. You enjoy working with cross-functional teams, analyzing complex data, building scalable applications, and driving continuous improvement through technology.\nKEY RESPONSIBILITIES:\nDesign and develop software tools, automation frameworks, and data-driven solutions to improve Product Engineering productivity and execution efficiency. \nDevelop and maintain data pipelines, data models, analytics workflows, and data-quality checks that support engineering operations and decision-making. \nAnalyze engineering and manufacturing data to identify trends, anomalies, risks, bottlenecks, yield opportunities, and improvement actions. \nBuild dashboards, notebooks, reports, and visualizations for KPI tracking, engineering analytics, and management reporting. \nDevelop intelligent applications using machine learning, generative AI, prompt engineering, natural-language processing, anomaly detection, or LLM-based approaches where appropriate. \nIntegrate applications with enterprise and engineering systems through REST APIs to improve data accessibility, traceability, task management, and knowledge sharing. \nDevelop scalable solutions for issue tracking, workflow management, operational reporting, and engineering knowledge retention. \nBuild or support lightweight web applications and user interfaces for analytics, automation, or AI-enabled engineering workflows. \nDefine validation, evaluation, logging, and monitoring approaches to ensure outputs are accurate, traceable, useful, and suitable for engineering use. \nCollaborate with stakeholders to gather requirements, define architectures, test solutions, support deployment, and drive user adoption. \nDocument designs, implementation steps, test results, user guides, limitations, risk controls, and best practices for maintainability and knowledge transfer. \nPREFERRED EXPERIENCES:\nExperience in Product Engineering, Software Engineering, Data Engineering, Analytics, Test Engineering, or a related technical discipline. \nPython and programming - Strong Python skills for data processing, automation, analytics, report generation, engineering-log analysis, or AI application development. Experience with C or another language is an advantage. \nData analysis and SQL - Strong SQL fundamentals and experience extracting, transforming, cleaning, validating, modeling, and analyzing engineering or manufacturing data. \nAI and machine learning - Practical knowledge of machine learning, generative AI, prompt engineering, NLP, anomaly detection, predictive analytics, or LLM applications. \nData visualization - Experience with Tableau, Power BI, matplotlib, Plotly, or equivalent tools for dashboards, yield/KPI tracking, analytics, and management reporting. \nWeb application development - Exposure to React, Vue, Flask, FastAPI, Django, or similar frameworks for building lightweight interfaces and applications is desirable. \nAPI and system integration - Experience using REST APIs to connect applications with Jira, Confluence, Teams, SharePoint, Snowflake, Microsoft 365, AI services, or other enterprise platforms. \nAgentic AI frameworks - Exposure to one or more agent or tool-calling frameworks or SDKs such as LangChain, LangGraph, OpenAI SDK, Semantic Kernel, CrewAI, AutoGen, or MCP is an advantage. \nCloud and data platforms - Exposure to Snowflake, Azure, AWS, Databricks, or similar enterprise and cloud data environments. \nLinux and deployment - Familiarity with Linux, virtual machines, application hosting, deployment, and runtime troubleshooting is desirable. \nDevOps and infrastructure - Experience with Git and exposure to CI/CD, Docker, Kubernetes, Terraform, logging, or monitoring is beneficial. \nEngineering domain - Understanding of semiconductor manufacturing, Product Engineering, silicon test, diagnostics, yield analysis, reliability, BISR/MBIST, wafer-map analysis, or product bring-up is highly desirable. \nCollaboration tools - Working familiarity with Jira, Confluence, Microsoft Teams, SharePoint, Outlook, Copilot, Excel, PowerPoint, and Word is advantageous. \nProfessional capabilities - Structured problem solving, attention to detail, proactive communication, clear technical documentation, strong learning agility, ownership, initiative, and ability to drive work from idea to implementation. \nACADEMIC CREDENTIALS:\nBachelor’s or Master’s in electrical engineering, computer engineering, or comparable disciplines \nLOCATION:\nSingapore\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nWe are seeking a highly motivated engineer to develop software, data, automation, and AI-driven solutions that improve Product Engineering productivity and decision-making. You will build tools, analytics, dashboards, and intelligent applications that help engineering teams work more efficiently and gain insights from complex manufacturing and engineering data.\nTHE PERSON:\nYou are a hands-on problem solver with strong software and data skills, a passion for automation and AI, and the ability to turn ideas into practical solutions. You enjoy working with cross-functional teams, analyzing complex data, building scalable applications, and driving continuous improvement through technology.\nKEY RESPONSIBILITIES:\nDesign and develop software tools, automation frameworks, and data-driven solutions to improve Product Engineering productivity and execution efficiency. \nDevelop and maintain data pipelines, data models, analytics workflows, and data-quality checks that support engineering operations and decision-making. \nAnalyze engineering and manufacturing data to identify trends, anomalies, risks, bottlenecks, yield opportunities, and improvement actions. \nBuild dashboards, notebooks, reports, and visualizations for KPI tracking, engineering analytics, and management reporting. \nDevelop intelligent applications using machine learning, generative AI, prompt engineering, natural-language processing, anomaly detection, or LLM-based approaches where appropriate. \nIntegrate applications with enterprise and engineering systems through REST APIs to improve data accessibility, traceability, task management, and knowledge sharing. \nDevelop scalable solutions for issue tracking, workflow management, operational reporting, and engineering knowledge retention. \nBuild or support lightweight web applications and user interfaces for analytics, automation, or AI-enabled engineering workflows. \nDefine validation, evaluation, logging, and monitoring approaches to ensure outputs are accurate, traceable, useful, and suitable for engineering use. \nCollaborate with stakeholders to gather requirements, define architectures, test solutions, support deployment, and drive user adoption. \nDocument designs, implementation steps, test results, user guides, limitations, risk controls, and best practices for maintainability and knowledge transfer. \nPREFERRED EXPERIENCES:\nExperience in Product Engineering, Software Engineering, Data Engineering, Analytics, Test Engineering, or a related technical discipline. \nPython and programming - Strong Python skills for data processing, automation, analytics, report generation, engineering-log analysis, or AI application development. Experience with C or another language is an advantage. \nData analysis and SQL - Strong SQL fundamentals and experience extracting, transforming, cleaning, validating, modeling, and analyzing engineering or manufacturing data. \nAI and machine learning - Practical knowledge of machine learning, generative AI, prompt engineering, NLP, anomaly detection, predictive analytics, or LLM applications. \nData visualization - Experience with Tableau, Power BI, matplotlib, Plotly, or equivalent tools for dashboards, yield/KPI tracking, analytics, and management reporting. \nWeb application development - Exposure to React, Vue, Flask, FastAPI, Django, or similar frameworks for building lightweight interfaces and applications is desirable. \nAPI and system integration - Experience using REST APIs to connect applications with Jira, Confluence, Teams, SharePoint, Snowflake, Microsoft 365, AI services, or other enterprise platforms. \nAgentic AI frameworks - Exposure to one or more agent or tool-calling frameworks or SDKs such as LangChain, LangGraph, OpenAI SDK, Semantic Kernel, CrewAI, AutoGen, or MCP is an advantage. \nCloud and data platforms - Exposure to Snowflake, Azure, AWS, Databricks, or similar enterprise and cloud data environments. \nLinux and deployment - Familiarity with Linux, virtual machines, application hosting, deployment, and runtime troubleshooting is desirable. \nDevOps and infrastructure - Experience with Git and exposure to CI/CD, Docker, Kubernetes, Terraform, logging, or monitoring is beneficial. \nEngineering domain - Understanding of semiconductor manufacturing, Product Engineering, silicon test, diagnostics, yield analysis, reliability, BISR/MBIST, wafer-map analysis, or product bring-up is highly desirable. \nCollaboration tools - Working familiarity with Jira, Confluence, Microsoft Teams, SharePoint, Outlook, Copilot, Excel, PowerPoint, and Word is advantageous. \nProfessional capabilities - Structured problem solving, attention to detail, proactive communication, clear technical documentation, strong learning agility, ownership, initiative, and ability to drive work from idea to implementation. \nACADEMIC CREDENTIALS:\nBachelor’s or Master’s in electrical engineering, computer engineering, or comparable disciplines \nLOCATION:\nSingapore\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. 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