Fullstack AI Architect
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Job Summary
Role & Responsibilities
- Design and own end-to-end architecture for full-stack innovation projects across the portfolio
- Define technical standards frameworks and design patterns to ensure scalability reliability and maintainability across engineering teams
- Champion the adoption of AI-powered development tools and agentic workflows to elevate engineering velocity and code quality org-wide
- Partner closely with product engineering leadership and cross-functional teams to translate experimental concepts into production-ready systems
- Lead technical discussions and decision-making on architecture technology selection and implementation approaches
- Mentor senior and mid-level engineers driving adoption of advanced development practices and emerging technologies
- Drive rapid prototyping initiatives and establish frameworks for iterative experimental development cycles
- Own critical/high-impact features and systems end-to-end from architecture and development through deployment monitoring and production support
- Evaluate build vs. buy decisions and assess emerging technologies (including AI/LLM tooling) for enterprise adoption
Required Qualifications
- 1215 years of professional software engineering experience including 3 years in an architect or technical leadership capacity with proven ownership of production systems at scale
- Deep expertise in full-stack architecture frontend frameworks backend services/microservices databases and cloud platforms (AWS/Azure/GCP)
- Strong working knowledge of AI code assistants and agentic development tools (Amazon Q GitHub Copilot Claude Code Gemini CLI Cursor or similar) with the ability to evaluate and drive their adoption across teams
- Proven experience owning High-Level Design (HLD) and Low-Level Design (LLD) for complex distributed systems
- Strong proficiency in one or more programming languages with a demonstrated track record of evaluating and adopting new technologies
- Ability to write review and enforce clean maintainable well-tested code and engineering best practices across teams
- Experience driving architecture decisions in ambiguous fast-paced innovation-driven environments
- Strong stakeholder management and communication skills able to influence both technical and business audiences
Required Skills:
Required Skills & Qualifications Project & Program Management Project planning estimation scheduling and execution MUST HAVE Risk issue dependency and change management MUST HAVE Resource planning and capacity management MUST HAVE Executive reporting and governance management MUST HAVE Agile & Scrum Scrum Master experience leading Agile teams MUST HAVE Velocity tracking sprint metrics and release planning MUST HAVE Backlog prioritization and sprint management MUST HAVE SAFe or Scaled Agile experience GOOD TO HAVE AI & Technology Delivery Experience managing AI/ML or Generative AI projects MUST HAVE Knowledge of Azure OpenAI AI platforms LLMs or enterprise AI solutions GOOD TO HAVE Experience managing cloud and modernization programs MUST HAVE Tools & Platforms JIRA and Confluence MUST HAVE Azure DevOps (ADO) MUST HAVE Microsoft Project / Smartsheet / equivalent planning tools MUST HAVE Miro Lucidchart or collaboration tools GOOD TO HAVE Leadership & Communication Excellent stakeholder management and communication skills MUST HAVE Strong facilitation and conflict resolution skills MUST HAVE Proactive issue identification and resolution MUST HAVE Experience 10 years of experience in Project Management Program Management or Scrum Master roles. 3 years of experience managing AI Data Analytics Generative AI or Digital Transformation initiatives. GOOD TO HAVE. PMP CSM PMI-ACP SAFe Scrum Master or equivalent certification GOOD TO HAVE.
