{"id":1402655,"url":"https://alion.io/job/kion-group-software-product-manager","title":"Software Product Manager","company":{"id":51782,"name":"KION Group","domain":"kiongroup.com","url":"https://alion.io/company/kion-group","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":78,"open_postings":41,"ghost_share":0,"stale_share":0.854,"repost_share":0.024,"time_to_fill_p50_days":42,"computed_at":"2026-10-02T05:45:00Z"}},"role":"Product","role_family":"Product","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Grand Rapids, United States","Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":102400,"max":128000,"currency":"USD","period":"year","gross":null,"usd_annual":128000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"AI Agents","optional":true},{"name":"Anomaly Detection","optional":true},{"name":"Digital Twin","optional":true}],"status":"live","first_seen_at":"2026-09-28T16:15:22Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-02T17:22:27Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Dematic is seeking a Product Manager, Industrial AI & Operational Intelligence to help define, deploy, and scale AI-driven capabilities within the Command Center platform. This individual will work closely with AI engineers, software development teams, implementation teams, and customers to identify practical industrial AI use cases, guide solution development, validate results in real operating environments, and ensure successful adoption across warehouse, distribution, manufacturing, and automation operations.This is not a traditional software product management role focused only on backlog grooming or roadmap administration. The role requires hands-on engagement across the full AI product lifecycle: use-case discovery, business case development, data and model readiness, pilot execution, customer validation, deployment support, change management, and commercialization. The successful candidate will be technically credible with AI and software teams, operationally credible with warehouse and manufacturing leaders, and commercially credible with customers, sales, and executive stakeholders.\nWe offer:\nCareer Development\nCompetitive Compensation and Benefits\nPay Transparency\nGlobal Opportunities\nDematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.\nThis policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.\nThe base pay range for this role is estimated to be $102,400-$128,000 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge, and skills.\nLearn More Here: https://www.dematic.com/en-us/about/careers/what-we-offer.\nTasks and Qualifications:\nWhat You Will Do\nAI Strategy & Use-Case Development\nIdentify high-value AI opportunities across warehousing, distribution, manufacturing, automation, and industrial operations.\nTranslate customer pain points into well-defined AI use cases with clear hypotheses, success criteria, adoption paths, and ROI expectations.\nCreate and maintain a prioritized AI use-case roadmap based on customer value, technical feasibility, data readiness, commercial potential, and deployment complexity.\nDefine the business requirements, product behavior, acceptance criteria, and operational KPIs needed to evaluate AI solutions in production environments.\nHelp separate meaningful customer value from AI hype by focusing on operational outcomes such as throughput, labor productivity, order fulfillment, availability, downtime reduction, inventory performance, and exception resolution.\nBusiness Direction for AI & Engineering Teams\nWork hand-in-glove with AI engineers and scientists, software architects, UX designers, and platform teams to guide product decisions and prioritize engineering work.\nProvide business context to technical teams so models, agents, analytics, and user experiences are developed around real operating problems rather than technology demonstrations\nReview solution outputs, recommendations, agent behaviors, and analytics workflows to ensure they are understandable, usable, and valuable for operational users.\nDrive alignment between AI capabilities and Command Center product strategy, including predictive visibility, operational recommendations, autonomous monitoring, root-cause analysis, optimization, and decision support.\nPartner with engineering leadership to define practical release plans, pilot readiness criteria, deployment constraints, and support expectations.\nCustomer Engagement & Deployment\nServe as the product lead during customer AI engagements, from discovery through pilot execution and production rollout.\nLead customer workshops to understand operational goals, constraints, data availability, tolerance for automation, decision rights, and success criteria.\nWalk skeptical customers through the AI process in a clear and grounded way, including what the solution can do, what it cannot do, how recommendations are generated, how results should be reviewed, and what human oversight remains in place.\nReview AI outputs with customers, operations teams, and internal stakeholders to refine use cases, improve trust, and identify product enhancements.\nSupport implementation teams with repeatable deployment playbooks, pilot plans, validation checklists, and adoption guidance.\nAI Validation, Trust & Governance\nDefine validation frameworks for measuring model quality, recommendation usefulness, business impact, user adoption, and customer confidence.\nEstablish feedback loops from customer deployments back into product, AI engineering, data engineering, and UX teams.\nHelp shape responsible AI practices for industrial deployments, including explainability, transparency, escalation paths, human review, auditability, and appropriate limits on automation.\nMonitor deployed AI capabilities and identify opportunities to improve accuracy, usability, operational fit, and customer value.\nEnsure AI solutions are positioned as practical decision-support tools that augment customer operations rather than opaque black-box systems.\nCommercialization & Market Enablement\nSupport sales, solution consulting, and commercial teams with customer-facing narratives, demonstrations, pilot proposals, business cases, proof points, and value assessments.\nDevelop practical messaging that explains AI capabilities in operational terms for customer executives, site leaders, IT leaders, and frontline operations stakeholders.\nCollaborate on packaging, pricing, deployment models, and post-sale adoption approaches for Command Center AI capabilities.\nBuild referenceable customer stories, repeatable use-case patterns, and lessons learned from early deployments.\nWhat We Are Looking For\n7+ years of experience in product management, solution consulting, industrial software, operational excellence, automation, supply chain technology, or a related role.\n3+ years of direct experience managing software products involving AI, machine learning, advanced analytics, optimization, and generative AI.\nExperience delivering technology solutions into industrial environments such as warehouses, distribution centers, manufacturing plants, material handling operations, or automated facilities.\nStrong working knowledge of operational KPIs such as throughput, productivity, order fulfillment, downtime, availability, labor utilization, equipment performance, inventory accuracy, and exception management.\nAbility to translate ambiguous business problems into structured use cases, product requirements, workflows, acceptance criteria, and measurable outcomes.\nStrong customer-facing communication skills, including the ability to explain technical concepts to non-technical stakeholders and build trust with skeptical customers.\nDemonstrated ability to lead cross-functional work across product, engineering, data science, implementation, sales, and customer teams.\nPreferred Qualifications\nExperience with WMS, WES, WCS, MES, industrial automation platforms, digital twins, industrial IoT, telemetry, or operational analytics platforms.\nFamiliarity with LLMs, AI agents, ML models, MLOps, data pipelines, forecasting, anomaly detection, root-cause analysis, causal AI, and simulation.\nExperience supporting pilots, proof-of-value programs, customer deployments, or post-sale adoption for enterprise software or industrial technology.\nAbility to evaluate data readiness and identify practical constraints related to data quality, integration, latency, context, ownership, and operational interpretation.\nMBA, engineering degree, supply chain degree, analytics degree, or equivalent practical experience.\nSuccess Profile\nTechnically credible with AI engineers and software architects, without needing to be the person building the models.\nOperationally credible with warehouse, manufacturing, maintenance, IT, and automation leaders.\nCommercially credible with customers, sales teams, and executive stakeholders.\nComfortable operating in ambiguity and turning early-stage AI concepts into deployable, repeatable product capabilities.\nAble to balance innovation with customer trust, operational risk, explainability, and adoption readiness.\nFocused on measurable business outcomes rather than AI terminology, demos, or technology for its own sake.\nThis is a hybrid role requiring proximity to one of our U.S. offices (Grand Rapids, MI; Atlanta, GA). Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.","description_format":"text","description_chars":8899,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Transportation & Logistics","Supply Chain"],"lifecycle":[{"event":"open","at":"2026-09-28T16:15:22Z"}],"liveness":{"score":70,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.695,"p_room":1,"age_days":3,"expected_fill_days":42,"reasons":["conf:13","stale_co","urgency","velocity","win:early","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":{"stated_usd_annual":128000,"is_top_pay":false},"html_url":"https://alion.io/job/kion-group-software-product-manager","json_url":"https://alion.io/job/kion-group-software-product-manager.json","meta":{"generated_at":"2026-10-03T00:44:13Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":436,"day_limit":5000,"remaining_today":4564,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}