Assoc. Dir. , Technical Product Management

Job description

Job Description Associate Director – Product Manager, Context & Semantics Foundations The Opportunity • Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. • Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. • Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company’s IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. Role OverviewThis role is part of a broader enterprise initiative to establish a Data Context Layer (DCL) — a foundational capability designed to provide consistent, reusable, and scalable context across enterprise data products. The DCL is intended to address challenges related to data fragmentation, lack of shared semantics, and inconsistent interpretation of data across systems and products. It establishes a unified layer for representing context, relationships, and meaning, enabling downstream products to operate with greater consistency, interoperability, and intelligence. In addition, the DCL plays a critical role in enabling agentic AI capabilities across the enterprise by providing the structured context and semantic grounding required for intelligent agents to operate reliably. This includes ensuring that agent-driven workflows and decisions are based on consistent, governed, and interpretable data context, reducing risks associated with fragmentation, ambiguity, and lack of control. Within this initiative, the Associate Director – Product Manager, Context & Semantics Foundations will own the product definition, development, and evolution of core context and semantics capabilities. These capabilities form the backbone for how data is understood, connected, and consumed across multiple products and platforms, and will be central to enabling governed, scalable, and reusable intelligent systems. The role operates at the intersection of product, architecture, and enterprise platforms, working closely with Enterprise Architecture, platform teams, and product leadership to build enterprise-grade context capabilities that support both traditional data products and emerging AI-driven use cases. Key ResponsibilitiesProduct Ownership – Context & Semantics FoundationsOwn the end-to-end product strategy, roadmap, and lifecycle for Context & Semantics capabilities within the Data Context Layer Define how context is modeled, represented, and consumed across products and platforms Ensure capabilities are designed as reusable building blocks supporting multiple downstream products and AI-driven workflows Context & Semantics Capability DevelopmentDefine and evolve core capabilities related to:Context modeling and representation Semantic abstraction and standardization Relationships across data entities and domains Drive standardization in how data meaning, relationships, and context are defined, governed, and reused Ensure consistency across products in how context is applied and interpreted Agentic AI Enablement & GovernanceEnable development of agentic AI capabilities by providing:Structured and reusable context models Consistent semantic definitions across domains Ensure that agent-driven workflows operate on governed, high-quality, and interpretable data context Support definition of guardrails that:Reduce ambiguity in decision-making by AI agents Improve traceability and explainability of outcomes Partner with broader teams to align context capabilities with enterprise AI governance expectations Alignment with Enterprise Architecture & PlatformsWork closely with Enterprise Architecture (EA) to:Define scalable and extensible context models Align semantics with enterprise data standards and reference architectures Partner with enterprise platform teams to ensure:Integration with underlying platforms Consistent implementation of context capabilities across systems Cross-Product EnablementEnsure Context & Semantics capabilities are:Designed for consumption across multiple products and use cases Embedded into product development lifecycles Enable product teams to leverage context capabilities without duplicating logic Drive adoption of standardized semantics across the product ecosystem Execution & DeliveryDrive end-to-end execution of Context & Semantics capabilities Work closely with engineering teams to:Translate product requirements into scalable solutions Ensure quality, performance, and extensibility of implementation Establish execution discipline through:Clear roadmaps Milestone tracking Alignment with broader DCL delivery plans Stakeholder & Product AlignmentEngage with product leaders to:Understand requirements related to data context and semantics Prioritize capabilities based on enterprise needs and use cases Act as the primary owner for context-related product decisions, trade-offs, and prioritization Expected OutcomesEstablishment of a scalable Context & Semantics Foundation within the Data Context Layer Consistent definition and reuse of data context and meaning across products and platforms Enablement of governed, interpretable, and scalable agentic AI capabilities Reduced duplication in how context is modeled and implemented Improved interoperability and alignment across enterprise data products Strong adoption of context capabilities across multiple product lines and use cases Experience & ProfileRequired Qualifications8+ years of experience in product management, data platforms, or related domains Strong understanding of:Data modeling and relationships Semantic concepts and abstraction layers Platform-based product development Experience working across:Product Engineering Architecture teams Preferred QualificationsExperience with data platforms, metadata systems, or semantic frameworks Exposure to enterprise data ecosystems and cross-domain data usage Experience in platform or foundational capability development Experience supporting or working with AI/ML-driven systems and workflows Experience working in global delivery environments Leadership CharacteristicsStrong product thinker with ability to translate abstract concepts into actionable capabilities Systems thinker who understands data as part of a connected enterprise ecosystem Ability to balance innovation (AI/agentic capabilities) with governance and control Collaborative leader who aligns product, architecture, engineering, and emerging AI initiatives Execution-focused with emphasis on delivery, adoption, and enterprise scale Who we are We are known as Merck & Co., Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, we have been bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to d