Enterprise Solution Architect

We are seeking a highly strategic, hands‑on Enterprise Solution Architect to spearhead the design, build, and delivery of cloud‑native B2C digital products, including next‑generation Agentic AI solutions. This is an elite leadership role within our Digital Engineering practice where you will look across multiple client engagements to define robust enterprise blueprints and drive modern engineering practices. You will work directly with client executives, business leaders, and product development teams to solve complex, real‑world business problems—not just fulfill technical requirements. Your mission starts with a deep understanding of the consumer domain, the business vision, and the end‑to‑end product development lifecycle before designing the solution. As an enterprise leader, you will govern architectural standards, mentor other architects, and own product delivery outcomes from concept to production‑grade deployment. Responsibilities Enterprise Architecture Strategy: Define and govern scalable, secure, and high‑performance B2C product architectures on Google Cloud Platform (GCP), ensuring alignment with enterprise‑wide standards. Agentic AI & LLM Orchestration: Architect and integrate autonomous, multi‑agent AI systems that can execute complex workflows, retrieve external data, and drive intelligent, context‑aware user interactions within B2C applications. End‑to‑End Product Build & Delivery: Actively lead the end‑to‑end product build, translating conceptual product roadmaps into production‑grade, resilient digital applications. Business & Product Alignment: Act as the primary technical bridge between business strategy and engineering execution; lead requirements‑gathering workshops and translate strategic business goals into clean functional specifications, product roadmaps, and user stories. System Blueprinting: Design the complete system architecture, including mobile/web front‑ends, event‑driven microservices, secure data persistence layers, and third‑party API integrations. GCP‑Native Design: Architect modern, cloud‑native services utilizing a range of GCP offerings (e.g., GKE, Cloud Run, BigQuery, Apigee) while ensuring the flexibility to design for multi‑cloud environments. Engineering Governance: Establish robust engineering standards for API design, schema definition, code quality, testing automation, and CI/CD pipelines to ensure continuous, high‑quality product deployments. Hands‑on Technical Leadership: Provide technical governance and coaching to cross‑functional product development teams on modern architecture, domain‑driven design, and robust coding standards. Qualifications 12+ years of experience in application architecture, software engineering, and cloud‑native system design. Strong Product Development Background: Proven hands‑on experience in the actual build, engineering, and launching of end‑to‑end, high‑scale consumer‑facing (B2C) products. Agentic AI Expertise: Practical experience designing systems using Agentic AI patterns, large language models (LLMs), and orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen) to build autonomous, action‑oriented product features. GCP Platform Expertise: Deep, hands‑on experience designing and deploying enterprise solutions natively on Google Cloud Platform (GCP). You must be able to articulate the "why" behind your architectural decisions and the trade‑offs considered. Highly Desirable Multi‑Cloud Versatility: Broad, hands‑on architectural and product delivery experience spanning multiple major cloud platforms (specifically AWS or Azure alongside GCP). Business Consultation & Strategy: Exceptional business acumen with experience leading technical and product scoping discussions with non‑technical business executives and product owners. Modern Architecture Mastery: Deep expertise in microservices, event‑driven architecture, API‑first principles, container orchestration (Kubernetes), and modern caching/database strategies (Relational and NoSQL). AI‑Native Tooling Proficiency: Familiarity or hands‑on experience leveraging AI‑native development tools (e.g., integrated coding assistants in VSCode, Cursor, etc.) to accelerate the product development lifecycle. Certification: Google Cloud certification (e.g., Professional Cloud Architect) is strongly preferred. Preferred Skills Modern Data Services: Experience working with modern enterprise data platforms (e.g., Databricks, Snowflake) to support application analytics and AI pipelines. Enterprise Security & IAM: Deep understanding of secure software development lifecycle (SSDLC), modern identity management systems (e.g., Okta, OAuth 2.0), and cloud compliance. Robust Caching Strategies: Real‑world experience implementing high‑performance caching layers (e.g., Redis, Memcached) to handle high‑traffic B2C product requirements. #J-18808-Ljbffr