Technical Product Manager

Agentic AI Integration Technical Product Manager, CAS CAS uses unparalleled scientific content, specialized technology and unmatched human expertise to help R&D organizations across Commercial, Government and Academic sectors create groundbreaking innovations that benefit the world. As the Scientific Information Solutions Division of the American Chemical Society, CAS manages the largest curated reservoir of scientific knowledge, and for 119 years, has helped innovators mine, assess and apply that information to keep businesses thriving. The CAS team is global, diverse, endlessly curious and strives to make actionable scientific insights accessible to innovators worldwide. CAS is currently seeking an Agentic AI Integration Technical Product Manager for CAS Connections. This position will be located in our headquarters in Columbus, Ohio. Job Summary CAS Connections brings trusted CAS scientific data and AI into the tools researchers already use. It is an integration framework — an enterprise-grade MCP (Model Context Protocol) server, API, and growing set of platform integrations — that exposes the CAS Content Collection, the CAS Registry®, CAS BioFinder, and the CAS Newton℠ agentic AI as native tools that any AI agent or R&D platform can call. It is how CAS meets scientists where they now work: in Claude, Microsoft Copilot, Cursor, and the laboratory and informatics platforms of partners such as Albert Invent, Sapio Sciences, Inductive Bio, Scilligence, and Wolfram Research. This is a senior individual-contributor role deeply integrated with the team that builds the AI powering CAS’s scientific information products. Unlike product managers who own a single application such as CAS SciFinder, CAS BioFinder, or CAS IP Finder, you will work across the full portfolio of CAS capabilities. Your mandate is to look across every service and capability CAS builds — including agentic features such as CAS Newton — and determine how best to package and deliver that value to customers through CAS Connections. This is a deeply technical, cross-cutting product role. You will own the CAS Connections technical surface end to end. That means product strategy, roadmap, and the technical design of the tool suite, the pre-built agent “skills,” the supported integration surfaces (MCP, API, agent-to-agent protocols, and pre-built partner integrations), and the enterprise authentication and entitlement model. You will be a heavy influence on the integration roadmap — which capabilities and which partners, from the largest platforms to smaller specialist players, CAS Connections targets — partnering closely with the product manager who owns that roadmap. Influence go-to-market for CAS Connections primarily through the product manager, which owns go-to-market for commercial partner relationships and related offerings — supplying technical and capability input to positioning, messaging, and the enterprise commercial model. Over time, take on more direct go-to-market for agentic AI integration offerings, working with CAS Custom Services, Sales, and Marketing. Success in this role requires the rare combination of technical depth, product instincts honed on platform and developer-facing products, a deep read on the market and how customers buy, the cross-functional leadership to drive a go-to-market motion through influence, and enough scientific fluency to be credible with the researchers and R&D platforms CAS serves. Job Accountabilities Lead the vision, strategy, and roadmap for CAS Connections across its technical surface area — the MCP server, REST APIs, agent-to-agent protocols, pre-built partner integrations, and the tool and skills catalog — and communicate that roadmap to leadership, partners, and the broader organization. Product-manage across the portfolio: partner with the product manager who owns the integration roadmap, and work with the application product managers, AI development leads, and technical leads for CAS SciFinder, CAS BioFinder, and CAS IP Finder, to shape which CAS capabilities and services (CAS Newton, scientific tools, predictive models, content collections) are exposed through CAS Connections, in what priority, and how they are delivered — always optimizing for customer value across products rather than for any single application. Translate scientific and customer workflows into technical product requirements: define the tools, the pre-built agent skills (for example patent landscape and freedom-to-operate, safety profiling, and bioactivity profiling), and the developer and agent experiences that make CAS capabilities reliable in an agentic context. Partner closely with engineers and data scientists on technical design — MCP tool and skill design, API and SDK ergonomics, single-sign-on and entitlement-based access control, agent-to-agent protocols, observability, and evaluation. Read architecture and code well enough to make sound trade-offs and hold credible technical conversations. Champion the enterprise-grade authentication and data-privacy model (enterprise SSO; private credentials and interactions), and shape the entitlement and usage-metering approach that protects CAS intellectual property while enabling customer value. Lead customer and market discovery with scientists, R&D and informatics teams, and partner platform organizations to understand how agent-mediated scientific workflows are evolving, and maintain a clear-eyed view of the competitive landscape, from general-purpose AI assistants to community-built scientific MCP servers. Exercise heavy influence on go-to-market for CAS Connections in partnership with key Product Management leaders and other relevant functions — enabling Sales and informing the enterprise commercial model; working with Marketing on positioning, messaging, and web presence; partnering with CAS Custom Services on custom and enterprise integrations; and coordinating with Content and Technology on capability exposure and the shared AI service architecture — with a path to own technical use-case go-to-market over time. Define and track the metrics that matter — adoption, active usage, retention, partner integrations live, and capability coverage — and use them to drive roadmap and investment decisions. Stay ahead of the fast-moving agentic-AI ecosystem (MCP, agent-to-agent protocols, major AI clients and platforms), drive innovation and ensure CAS Connections remains broadly compatible and out in front of the standards customers expect. Required Qualifications 8+ years of product management experience, including senior or principal ownership of technical, platform, API, or developer-facing products delivered end to end. Demonstrated technical depth: the ability to reason fluently about APIs, authentication and SSO, integration protocols (such as MCP or comparable standards), and modern AI/agent architectures; to write clear technical specifications; and to partner with engineers as a credible technical peer, including reading code and architecture well enough to make trade-offs. Hands-on understanding of large language models and agentic AI — how agents, tools, retrieval, and clients such as Claude, Microsoft Copilot, and Cursor work in practice — and a genuine enthusiasm for building in this space. A track record across the full go-to-market lifecycle — working with Sales, Marketing, and partnerships to bring products to market and grow adoption — and the ability to drive go-to-market through influence, not solely managing a backlog. Experience with platform, ecosystem, or third-party integration products, including managing partner or developer relationships. Proven ability to lead and influence across functions without direct authority, and to coordinate delivery across multiple teams and stakeholders. The ability to build credibility with scientific and R&D users — reasoning about scientific workflows accurately enough to make sound product decisions for an audience of working scientists. Strong written and verbal communication skills, with the ability to work effectively across both technical and commercial teams. A degree in a scientific discipline relevant to CAS’s customer domains (chemistry, life sciences, materials science, or a related field), giving deeper command of the science behind the product. Direct experience with the Model Context Protocol, agent-to-agent protocols, or agent tool and skill design. Domain experience in scientific information, chemistry, pharma/biotech, or R&D informatics. Experience with enterprise authentication and entitlement systems (SSO, OAuth/OIDC, SAML) and with usage-based or enterprise commercial models for data and API products. Experience building developer platforms, SDKs, documentation, or partner programs. Familiarity with agentic software-development tools (for example Claude Code) as part of the daily workflow. Experience defining evaluation and quality frameworks for AI/agent systems. #J-18808-Ljbffr