We are seeking an experienced Enterprise Digital Build & AI Architect to lead the design and delivery of enterprise-scale digital platforms, AI-enabled products, and agentic AI initiatives. This role requires deep expertise in cloud-native architectures, BSS/OSS ecosystems, and a product-centric approach to platform design.
Key Qualifications
- Core Architecture & Product Engineering: 12+ years across architecture, product design, development, integration, and enterprise-scale solution delivery; 5+ years in product-centric architecture; strong experience architecting large-scale, distributed, cloud-native enterprise solutions; proven expertise in BSS/OSS ecosystems, enterprise digital platforms, and complex system integrations.
- Agentic AI & Intelligent Systems: Expert in agentic AI architectures (autonomous and semi-autonomous agents) for enterprise use cases; hands-on experience with ADK for designing, orchestrating, and governing intelligent agents; understanding of A2A communication, collaboration, and workflow orchestration; experience implementing MCP for grounding, tool usage, memory, and secure context exchange; familiarity with Google Agentic AI ecosystem (Gemini models, Vertex AI, agent frameworks, tool integrations); applying CBVA principles to translate AI capabilities into measurable business outcomes.
- Digital, Cloud & Integration: Expertise in cloud platforms (GCP preferred; AWS/Azure acceptable); API-led, event-driven, and streaming architectures; define integration patterns across CRM, Order Management, Billing, Inventory, Payments, Identity, and Partner ecosystems; knowledge of TMF, MEF, ITIL, IETF, IEEE 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; 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 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; meet 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 promote architectural best practices across product, cloud, and AI domains.
- Generic Managerial Skills: Strong stakeholder management with 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.
Pre-Screening Questionnaire
- Describe your experience designing and delivering Agentic AI solutions in an enterprise environment.
- What frameworks or toolkits (ADK, MCP, A2A) have you used to build and govern AI agents?
- How have you applied CBVA or value-based architecture to measure business impact of AI or product initiatives?
- Experience architecting large-scale product platforms integrated with BSS/OSS and digital channels.
Education & Experience: Total experience: 12-14 years; mid-senior level. Must have .NET experience. Bachelor’s degree in Computer Science, Engineering, or a related field.
Additional details: Open position: 1 • Relocation assistance: No • Visa sponsorship eligibility: No
