{"id":679661,"url":"https://alion.io/job/articul8-builder-product-manager-ai-platform-agentic-workflows","title":"Builder Product Manager, AI Platform & Agentic Workflows","company":{"id":669038,"name":"Articul8","domain":"articul8.ai","url":"https://alion.io/company/articul8","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"D","score":40,"open_postings":20,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Product","role_family":"Product","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dublin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":104000,"max_usd":207000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":737},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"RAG","optional":false},{"name":"Multimodal AI","optional":true}],"status":"live","first_seen_at":"2026-06-25T16:32:19Z","employer_posted_date":"2026-06-25","last_verified_at":"2026-10-24T23:57:13Z","board_verified":true,"closed_at":null,"days_open":121,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":120},"description":"About Us:\nArticul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform - combining domain-specific models, autonomous agentic reasoning (ModelMesh™), reliable model evaluation (LLM-IQ™), and multimodal understanding - serves regulated industries such energy, semiconductor, finance, aerospace, supply chain, and more. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand.\nJob Description:\nArticul8 AI is hiring a Builder Product Manager, AI Platform & Agentic Workflows to own the delivery of customer-facing AI workflow experiences: multi-agent missions, natural-language query over domain knowledge graphs, SDK-based hyper-personalized applications, agents, and MCP-enabled tools.\nThis is a hands-on, “build-and-ship” product role. You will work directly with customers and internal teams to prototype solutions, validate workflows end-to-end, troubleshoot issues, and translate real-world needs into clear, actionable requirements for engineering and applied research. You will use a state-of-the-art AI platform and feed customer requirements directly to the platform teams to improve both the end-use application and base platform capabilities.\nKey Responsibilities\nCustomer Ownership & Product Delivery\nServe as the customer-facing owner for delivering agentic missions for assigned enterprises, including weekly demos, product updates, technical Q&A, and domain/SME working sessions.\n\nTranslate customer needs into product requirements, technical feature requests, acceptance criteria, edge cases, data dependencies, and test scenarios.\n\nDrive delivery from prototype to production-ready quality, balancing customer outcomes with platform constraints and timelines.\n\nDistill customer requests, bugs, platform gaps, and technical constraints into prioritized delivery plans.\n\nHands-On Building & Prototyping\nBuild mission-specific experiences using the Articul8 platform, SDK, agents, APIs, and MCP-enabled tools.\n\nCreate prototypes, demos, internal tools, interaction flows, and proof-of-concept applications to make customer workflows tangible and testable.\n\nIdentify what can be delivered with existing capabilities, where SDK extensions are required, and where platform gaps require new engineering investment.\n\nTesting, Quality & Troubleshooting\nOwn the quality bar across dev, staging, and customer-facing environments.\n\nTest end-to-end workflows (agent outputs, model behavior, tool calls, data ingestion, UI flows, knowledge grounding, and SDK experiences).\n\nReproduce failures, isolate root causes, and file high-signal bug reports and triage notes for engineering.\n\nPartner closely with the engineering team to validate fixes and confirm what has landed in source vs. what has been deployed and verified.\n\nDifferentiate among product gaps, data issues, model behavior, agent orchestration failures, tool-calling problems, UI gaps, environment mismatches, and engineering defects.\n\nApplied Research Collaboration\nPartner with applied research to clarify data needs for training, evaluation, fine-tuning, and experimentation.\n\nHelp collect, organize, and document datasets needed for training and testing.\n\nSupport the data creation process by defining realistic workflow scenarios, edge cases, expected outputs, and failure modes.\n\nTest models, inspect outputs, compare results against expectations, and provide structured feedback.\n\nDocumentation, Competitive Analysis & Communication\nProduce high-quality product and technical documentation: requirements, workflow guides, SDK notes, test plans, troubleshooting guides, handover docs, release notes, and demo scripts.\n\nAnalyze competitor offerings across enterprise AI platforms, agents, MCP ecosystems, workflow automation, knowledge graphs, and evaluation tooling; translate insights into product recommendations.\n\nCreate customer-ready materials including walkthroughs, demos, technical explainers, and presentations.\n\nMentor interns with structured feedback and product judgment.\n\nRequired Qualifications\n4+ years of overall professional experience in product management (or product-adjacent technical roles such as engineering, solutions engineering, or technical implementation), with a demonstrated track record of shipping complex platform products end-to-end.\n\nStrong technical foundation across software systems, APIs, SDKs, data workflows, AI applications, enterprise platforms, and/or cloud-based systems.\n\nHands-on experience building prototypes, workflow applications, demos, internal tools, agentic workflows, or customer proof-of-concepts.\n\nFamiliarity with agents and tool-calling (including MCP-style tools), LLM applications, RAG, knowledge systems, and AI copilots.\n\nAbility to translate ambiguous customer needs into clear technical requirements and acceptance criteria for engineering.\n\nDemonstrated ability to test product features end-to-end, troubleshoot issues, reproduce bugs, and provide structured feedback.\n\nStrong written and verbal communication, documentation skills, and comfort presenting to technical and non-technical stakeholders.\n\nComfort operating in a fast-moving environment with evolving customer needs, research priorities, and platform capabilities.\n\nPreferred Qualifications\nExperience running customer demos, stakeholder updates, and technical product walkthroughs.\n\nExperience reading source code, reviewing repositories, and validating whether fixes have landed across branches/environments.\n\nExperience creating synthetic datasets, evaluation sets, prompt test suites, or domain-specific training examples.\n\nExperience partnering with researchers, data scientists, ML engineers, or applied AI teams.\n\nExperience with knowledge graphs, natural-language query systems, agentic copilots, RAG workflows, or AI evaluation.\n\nExposure to enterprise domains such as manufacturing, energy, financial services, semiconductors, telecom, healthcare, industrial operations, supply chain, or engineering workflows.\n\nExperience creating product videos or demo walkthroughs.\n\nMBA preferred but not required.\n\nProfessional Attributes (Code42):\nPractice Humility: You ask questions even when you think you know the answer. You seek feedback early, learn from anyone regardless of title, and treat every experiment - especially the failures - as data.\n\nBias for Outcomes: You measure your work by what changed, not what you tried. You ship results, not slide decks. When a deadline is real, you find a way.\n\nCare Deeply: You treat every problem as yours to solve. You review your own work with the rigor you'd want from a reviewer. You help teammates without being asked.\n\nDare to Do the Impossible & Embrace Scarcity: You set goals that make you uncomfortable. When told something can't be done, you find a way or a better question. Constraints sharpen your thinking, not slow it down.\n\nBuild a Better World: You believe AI should make things meaningfully better for real people. 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