{"id":58576,"url":"https://alion.io/job/lumentum-director-ai-engineering-manufacturing","title":"Director, AI Engineering - Manufacturing","company":{"id":5264,"name":"Lumentum","domain":"lumentum.com","url":"https://alion.io/company/lumentum","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":38,"ghost_share":0,"stale_share":0.921,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Pathum Thani, Thailand","Shenzhen, China","Sagamihara, Japan"],"countries":["TH","CN","JP"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":64000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":4188},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"Statistical Process Control","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-08-14T00:00:00Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-11-04T03:29:41Z","board_verified":true,"closed_at":null,"days_open":82,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":82},"description":"It's fun to work in a company where people truly BELIEVE in what they're doing!\nWe're committed to bringing passion and customer focus to the business.\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!\nRole Summary\nWe are seeking a senior engineering and AI/ML leader to build and lead a distributed team of AI/ML engineers supporting manufacturing sites across the company. Based in Bangkok or the UK or Canada and reporting to the Chief AI Officer, this role will translate high-value manufacturing problems into reliable, scalable AI systems that improve productivity, quality, yield, equipment performance, and operational decision-making.\nThe ideal candidate brings 15+ years of experience across engineering management, software engineering, AI/ML systems, and data science, combined with deep practical knowledge of manufacturing environments. This leader must be equally comfortable setting technical direction, coaching engineers, partnering with plant and business leaders, and working close to the factory floor to move solutions from discovery through production adoption.\nLeadership Scope\nLead, grow, and develop a distributed team of AI/ML engineers who work across manufacturing sites and solve site-specific operational problems.\nEstablish the technical vision, engineering standards, delivery practices, and talent strategy for manufacturing AI across the organization.\nCreate a strong partnership model with plant leadership, manufacturing engineering, process engineering, yield, quality, operations, IT, and enterprise data teams.\nBalance local site responsiveness with reusable platforms, common architectures, shared components, and responsible AI practices that scale across plants.\nKey Responsibilities\nSet and execute a multi-year roadmap for AI/ML applications in manufacturing, aligned to business priorities and measurable operational outcomes.\nIdentify and prioritize high-impact opportunities across process optimization, yield improvement, visual inspection, defect classification, predictive maintenance, anomaly detection, root-cause analysis, quality, scheduling, and engineering productivity.\nGuide the architecture, design, development, validation, deployment, and lifecycle management of production-grade AI/ML systems used in manufacturing workflows.\nDefine engineering patterns for data pipelines, feature and model management, experiment tracking, APIs, user interfaces, monitoring, cybersecurity, reliability, and model performance management.\nEnsure solutions work with real manufacturing data and systems, including MES, SPC, QMS, equipment and sensor data, inspection systems, yield systems, ERP, databases, engineering reports, and other structured and unstructured sources.\nDrive disciplined problem definition and value measurement, connecting technical delivery to improvements in cycle time, throughput, yield, scrap, quality, cost, safety, and decision speed.\nPartner with site teams to understand workflows, constraints, process variation, data quality, user needs, and adoption barriers; ensure solutions are usable by engineers, operators, and business stakeholders.\nBuild and maintain strong relationships with senior manufacturing and technology leaders, communicating technical tradeoffs, risks, investment needs, and results with clarity.\nPromote effective use of classical machine learning, deep learning, computer vision, optimization, statistical methods, LLMs, and generative AI where they are fit for purpose.\nEstablish governance for responsible, secure, explainable, and maintainable AI in manufacturing, including validation, human oversight, change control, and production support.\nRequired Qualifications\n15+ years of progressive experience in software engineering, AI/ML engineering, data science, or a closely related technical discipline, including significant leadership experience.\nBachelor's or master's degree in engineering, computer science, electrical engineering, industrial engineering, data science, or a related field; advanced technical education is preferred.\nDeep hands-on understanding of software engineering practices, distributed systems, cloud or edge architectures, APIs, data platforms, testing, observability, security, and production operations.\nPractical knowledge of manufacturing processes, process variation, yield, quality systems, equipment data, inspection, traceability, root-cause analysis, and the realities of plant operations.\nWillingness and ability to travel 30% or more to manufacturing sites and partner locations.\nPreferred Qualifications\nExperience in semiconductor, photonics, electronics, optical components, precision manufacturing, or other high-volume advanced manufacturing environments.\nExperience with manufacturing software and data ecosystems such as MES, SPC, QMS, ERP, equipment automation, inspection platforms, historian systems, and yield management systems.\nExperience scaling AI/ML capabilities across multiple plants, regions, or business units with different processes, data maturity, and operating models.\nExperience applying generative AI, knowledge retrieval, agentic workflows, or LLM-enabled tools to manufacturing, engineering, quality, or operations use cases.\nWe are an equal opportunity employer and value diversity at our company.\nWe do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.\nWe will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.\nPlease contact us to request 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