Enterprise Digital Build & AI-Architect (73448-1)
Velvet Ledger Workforce
Job Description
Job Description
Enterprise Digital Build & AI-Architect
Total Exp: 12- 14 Years
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 (GCP 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. Roles & Responsibilities
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.
Generic Managerial Skills, If any
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.
Key Words to search in Resume
Agentic AI, ADK, A2A, MCP, Google Agentic Ecosystem, Gemini, Vertex AI, Product Architecture, Enterprise Architecture, AI Agents, BSS, OSS, Digital Platforms, CBVA, Cloud-Native, API-led Architecture.
Vacancy posted 24 days ago
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