What are the responsibilities and job description for the Enterprise Digital Build & AI-Architect position at Jobs via Dice?
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Must Have Technical/Functional Skills
Core Architecture & Product Engineering
Product & Technology Leadership
Must Have Technical/Functional Skills
Core Architecture & Product Engineering
- 12 years of experience across architecture, product design, development, integration, and enterprise-scale solution delivery.
- 5 years of experience in Product-centric architecture, driving platform-based and domain-aligned product models.
- Strong experience architecting and designing large-scale, distributed, cloud-native enterprise solutions.
- Proven expertise in BSS/OSS ecosystems, enterprise digital platforms, and complex system integrations.
- Agentic AI & Intelligent Systems (Key Enhancement)
- Expert in Agentic AI architectures, including autonomous and semi-autonomous agents for enterprise use cases.
- Hands-on experience with ADK (Agent Development Kit) for designing, orchestrating, and governing intelligent agents.
- Strong understanding of A2A (Agent-to-Agent) communication patterns, collaboration, and workflow orchestration.
- Experience implementing MCP (Model Context Protocol) for agent grounding, tool usage, memory, and secure context exchange.
- Deep familiarity with the Google Agentic AI ecosystem, including Gemini models, Vertex AI, agent frameworks, and tool integrations.
- Experience applying CBVA (Customer / Cognitive Business Value Architecture) principles to translate AI capabilities into measurable business outcomes.
- Digital, Cloud & Integration
- Expertise in cloud platforms (Google Cloud Platform preferred; AWS/Azure acceptable) with focus on AI-native and data-driven architectures.
- Strong experience with API-led, event-driven, and streaming architectures.
- Define integration patterns across CRM, Order Management, Billing, Inventory, Payments, Identity, and Partner ecosystems.
- Knowledge of enterprise and industry standards such as TMF, MEF, ITIL, IETF, IEEE is highly desirable.
- Product, Analytics & Experience
- Own architecture vision for B2C / B2B / B2B2X product journeys including acquisition, onboarding, fulfillment, and lifecycle management.
- Embed AI-driven personalization, analytics, experimentation (A/B), accessibility, and performance SLOs into digital products.
- Enable sales and operations productivity using AI agents for lead scoring, recommendations, forecasting, and automation.
Product & Technology Leadership
- Define and own the end-to-end Product & Technology architecture vision, aligning business capabilities, products, platforms, and AI systems.
- Act as a trusted advisor to business leaders, product owners, and engineering teams on AI-first and product-centric transformation.
- Drive modernization from traditional systems to agent-enabled, composable, and platform-driven architectures.
- Agentic AI Solution Architecture
- Design and govern enterprise-grade Agentic AI solutions, including agent roles, autonomy boundaries, safety, observability, and compliance.
- Define reference architectures using ADK, MCP, and A2A patterns for scalable, secure, and interoperable agent ecosystems.
- Lead PoCs, pilots, and production rollouts of AI agents integrated with enterprise systems and digital channels.
- Delivery & Execution
- Engage across the full lifecycle from intake and discovery to architecture, delivery, and optimization to ensure solutions align with enterprise standards.
- Facilitate architecture and design workshops; translate business problems into product and AI-enabled system designs.
- Collaborate with platform architects, engineering leads, data scientists, and DevOps teams to ensure cohesive execution.
- Governance, Quality & Value Realization
- Ensure solutions are secure, operable, maintainable, and scalable, meeting non-functional requirements (performance, reliability, security).
- Apply CBVA-driven metrics to track ROI, adoption, productivity, and business impact of AI and product initiatives.
- Mentor teams and influence architectural best practices across product, cloud, and AI domains.
- Strong stakeholder management with the ability to communicate effectively at executive, product, and engineering levels.
- Proven experience leading large, matrixed, multi-vendor teams.
- Ability to balance strategic vision with hands-on architectural depth.