--- title: 'Builder Product Manager, AI Platform & Agentic Workflows at Articul8' canonical: 'https://feeny.ai/job/builder-product-manager-ai-platform-agentic-workflows-articul8-dublin-26fm156mng11' type: 'job' last_seen: '2026-09-10' --- # Builder Product Manager, AI Platform & Agentic Workflows at Articul8 - **Company:** Articul8 - **Location:** Dublin, Ireland - **Employment:** full-time - **Posted:** 2026-06-25 - **Last confirmed live:** 2026-09-10 - **Apply:** https://jobs.ashbyhq.com/articul8/268b3448-3671-4c4c-a75b-c1227865f1c1/application **Skills:** Product Management, Software Systems, APIs, SDKs, Data Workflows, AI Applications, Enterprise Platforms, Cloud-based Systems, Prototyping, Workflow Applications, Agent Workflows, MCP-style Tools, LLM Applications, RAG, Knowledge Systems, AI Copilots, Testing, Troubleshooting, Documentation, Knowledge Graphs > The Builder Product Manager owns the delivery of customer-facing AI workflow experiences, including multi-agent missions and natural-language query over domain knowledge graphs. This hands-on role involves prototyping solutions, validating workflows, and translating customer needs into technical requirements for eng... ## Job description About Us: Articul8 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. Job Description: Articul8 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. This 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. ## Key Responsibilities - Customer Ownership & Product Delivery - Serve 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. - Translate customer needs into product requirements, technical feature requests, acceptance criteria, edge cases, data dependencies, and test scenarios. - Drive delivery from prototype to production-ready quality, balancing customer outcomes with platform constraints and timelines. - Distill customer requests, bugs, platform gaps, and technical constraints into prioritized delivery plans. - Hands-On Building & Prototyping - Build mission-specific experiences using the Articul8 platform, SDK, agents, APIs, and MCP-enabled tools. - Create prototypes, demos, internal tools, interaction flows, and proof-of-concept applications to make customer workflows tangible and testable. - Identify what can be delivered with existing capabilities, where SDK extensions are required, and where platform gaps require new engineering investment. - Testing, Quality & Troubleshooting - Own the quality bar across dev, staging, and customer-facing environments. - Test end-to-end workflows (agent outputs, model behavior, tool calls, data ingestion, UI flows, knowledge grounding, and SDK experiences). - Reproduce failures, isolate root causes, and file high-signal bug reports and triage notes for engineering. - Partner closely with the engineering team to validate fixes and confirm what has landed in source vs. what has been deployed and verified. - Differentiate among product gaps, data issues, model behavior, agent orchestration failures, tool-calling problems, UI gaps, environment mismatches, and engineering defects. - Applied Research Collaboration - Partner with applied research to clarify data needs for training, evaluation, fine-tuning, and experimentation. - Help collect, organize, and document datasets needed for training and testing. - Support the data creation process by defining realistic workflow scenarios, edge cases, expected outputs, and failure modes. - Test models, inspect outputs, compare results against expectations, and provide structured feedback. - Documentation, Competitive Analysis & Communication - Produce high-quality product and technical documentation: requirements, workflow guides, SDK notes, test plans, troubleshooting guides, handover docs, release notes, and demo scripts. - Analyze competitor offerings across enterprise AI platforms, agents, MCP ecosystems, workflow automation, knowledge graphs, and evaluation tooling; translate insights into product recommendations. - Create customer-ready materials including walkthroughs, demos, technical explainers, and presentations. - Mentor interns with structured feedback and product judgment. Required Qualifications - 4+ 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. - Strong technical foundation across software systems, APIs, SDKs, data workflows, AI applications, enterprise platforms, and/or cloud-based systems. - Hands-on experience building prototypes, workflow applications, demos, internal tools, agentic workflows, or customer proof-of-concepts. - Familiarity with agents and tool-calling (including MCP-style tools), LLM applications, RAG, knowledge systems, and AI copilots. - Ability to translate ambiguous customer needs into clear technical requirements and acceptance criteria for engineering. - Demonstrated ability to test product features end-to-end, troubleshoot issues, reproduce bugs, and provide structured feedback. - Strong written and verbal communication, documentation skills, and comfort presenting to technical and non-technical stakeholders. - Comfort operating in a fast-moving environment with evolving customer needs, research priorities, and platform capabilities. ## Preferred Qualifications - Experience running customer demos, stakeholder updates, and technical product walkthroughs. - Experience reading source code, reviewing repositories, and validating whether fixes have landed across branches/environments. - Experience creating synthetic datasets, evaluation sets, prompt test suites, or domain-specific training examples. - Experience partnering with researchers, data scientists, ML engineers, or applied AI teams. - Experience with knowledge graphs, natural-language query systems, agentic copilots, RAG workflows, or AI evaluation. - Exposure to enterprise domains such as manufacturing, energy, financial services, semiconductors, telecom, healthcare, industrial operations, supply chain, or engineering workflows. - Experience creating product videos or demo walkthroughs. - MBA preferred but not required. Professional Attributes (Code42): - Practice 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. - Bias 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. - Care 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. - Dare 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. - Build a Better World: You believe AI should make things meaningfully better for real people. You hold yourself accountable not just for whether your model works, but for what it does in the world. ## About Articul8 ## Company Overview - **One-liner**: Articul8 provides a full-stack domain-specific generative AI platform for enterprises in regulated industries, enabling them to build expert-level AI applications within their own IT environments. - **Entity Type**: Private (Series B) - **Headquarters**: Dublin, California, USA - **Founded**: 2024 - **Founders**: Arun K. Subramaniyan ## Core Business - **Primary industry/industries**: Enterprise AI, Generative AI, Domain-Specific AI - **Target customers**: Large enterprises in regulated industries including energy, manufacturing, aerospace, semiconductors, and financial services (B2B, Enterprise) - **Mission or purpose statement**: To transform enterprise data and expertise into powerful engines of growth, value, and impact by making it straightforward for companies to build sophisticated, enterprise-scale, and expert-level GenAI applications that encode their domain expertise. ## Products & Services - **Articul8 Platform**: A full-stack GenAI platform that processes enterprise data into AI applications, facilitating decision-making, data automation, and adherence to security and privacy standards. It features autonomous agentic reasoning, model evaluation and dynamic routing (LLM-IQ™), and a proprietary ModelMesh™ for multi-agent collaboration. - **Domain-Specific Models (DSMs)**: - **A8-Energy**: Developed with EPRI; trained on 10,000+ specialized energy datasets for expert reasoning in the energy sector. - **A8-SupplyChain**: Optimized for manufacturing and supply chain operations; reasons over complex technical documentation without data replication. - **A8-Fin**: Finance-focused DSM for tasks such as tabular analysis, portfolio management, and compliance. - **A8-Semicon**: Verilog-capable DSM for semiconductor engineering, integrating domain knowledge with reasoning for complex chip design workflows. - **Hyper-Personalized Agent Models**: Developing hyper-personalized agents for enterprise users. ## Market Standing - **Valuation/Market Cap**: $500 million pre-money valuation (Series B, January 2026) - **Key Metric**: Total funding of $35M raised (Series B, first tranche); $100 million in total contract value; projected annual recurring revenue of just over $57 million for 2026 - **Notable Investors/Partners**: Adara Ventures (lead), Aditya Birla Ventures, Accel, Peak XV Partners, NXC, and 14+ others. Partners include Nvidia, Google Cloud, AWS, and Databricks. Customers include Hitachi Energy, AWS, Franklin Templeton, Intel, AIAA, Itochu Techno-Solutions Corporation, Uptycs, and NIQ. - **Growth Signals**: Revenue-positive with 29 paying customers; 5x valuation increase from Series A ($100M post-money) to Series B ($500M pre-money); expanding internationally with focus on Europe and Asia (Japan, South Korea, India); recognized by Gartner as a Tech Innovator in Domain-Specific AI for Manufacturing and Energy. ## Competitive Advantages - **Domain-Specific Focus**: Unlike general-purpose models, Articul8’s DSMs are purpose-built for regulated industries, achieving 90%+ accuracy versus ~60% for competing models in proprietary benchmarks, and 28% more accurate than leading general LLMs. - **Enterprise-Grade Security**: SOC 2 Type II compliant with certified security and confidentiality standards, observability, auditability, and traceability at every step. - **Cost Efficiency**: 3.5x cheaper than best open-source models, with a 2x performance boost over the latest open-source state-of-the-art models. - **Proven Performance**: Matches or exceeds proprietary models like Google Flash 2.0 and GPT-4o at a fraction of the compute cost. - **Customer Lock-In**: Deep integration into customer IT environments and domain-specific workflows creates high switching costs. ## Strategic Focus - **International Expansion**: Scaling operations in Europe (backed by Adara Ventures and the European Investment Fund) and Asia (Japan, South Korea, India). - **Heritage AI Venture**: Raising $30-50 million for an India-based AI entity focused on traditional knowledge systems (Sanskrit, classical Indian languages) with applications in drug discovery, metallurgy, healthcare, and education. - **Product Development**: Expanding research and product development, particularly in agentic reasoning systems and hyper-personalized models. - **Marketplace Availability**: Available on AWS, Microsoft Azure, Google Cloud Platform, and Databricks to simplify deployment and integration. ## Why Work Here - **Culture**: 80% of the 75-person team is focused on R&D, indicating a strong engineering and research culture. The company is revenue-positive and not cash-strapped, providing stability. - **Remote/Hybrid Policy**: Offers remote and hybrid roles across offices in Dublin, CA (USA), Brazil, and India. - **Notable Perks**: Opportunity to work on cutting-edge domain-specific AI for regulated industries; involvement in a high-growth spinout from Intel with strong backing from top-tier VCs; chance to contribute to heritage AI initiatives preserving ancient knowledge systems. - **Engineering Culture**: Emphasis on autonomous decisions and actions, automated data intelligence, and building expert-level GenAI applications. Roles include Applied AI Researchers, Software Engineers, and Infrastructure Engineers. ## Sources 1. [articul8.ai](https://www.articul8.ai/) 2. [cbinsights.com](https://www.cbinsights.com/company/articul8-ai) 3. [techcrunch.com](https://techcrunch.com/2026/01/07/intel-spin-off-articul8-is-halfway-to-70m-ai-funding-round-at-500m-valuation/) 4. [builtin.com](https://builtin.com/company/articul8-ai) 5. 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