Overview You will own the end-to-end design of a major GenAI platform, aligning AI system architecture with enterprise standards. You collaborate with product, engineering, data science, cloud and control teams to deliver secure, scalable AI solutions. You define reference architectures, integration contracts, and non-functional requirements, ensuring production-grade, compliant systems. This role combines hands-on architecture with governance, risk management, and cross-pod guidance to enable enterprise AI at scale. A strong hook is shaping reusable patterns for RAG, model serving, and AI workflows to drive transformative outcomes.
Compensation / Benefits- 401K with company match
- comprehensive insurance coverage
- paid time off
- Employee Assistance Program
- incentive compensation including performance-based awards
- tax-advantaged savings plans
Responsibilities- Own end-to-end architecture and system design for a major AI platform domain, including model integration, orchestration, APIs, data flows, and downstream system interactions
- Define and implement reference architectures, design standards, integration contracts, and non-functional requirements (NFRs) for the platform area
- Translate business and product requirements into scalable, secure, resilient, and maintainable AI solution designs
- Partner with business stakeholders, product managers, engineers, data scientists, platform teams, and security teams to deliver enterprise-ready AI systems
- Design solutions leveraging cloud architecture principles on AWS, Azure, or Google Cloud, ensuring interoperability, scalability, observability, and operational readiness
- Establish reusable architecture patterns for RAG, model serving, prompt workflows, agentic AI workflows, and AI application integration
- Ensure alignment with Responsible AI, model governance, data handling, compliance, testing, risk, and production control requirements
- Conduct architecture assessments, technical design reviews, and proof-of-concept evaluations for new AI use cases and platform capabilities
- Review solution designs across pods and provide guidance on architecture decisions, trade-offs, and standards adherence
- Partner with engineering and DevSecOps teams to support production readiness, release architecture, monitoring, and scalability planning
Key requirements- Bachelor's degree in Computer Science, Computer Information Systems, Engineering, Mathematics, or a related discipline; Master's degree preferred
- 8-14 years of experience in solution architecture, enterprise application architecture, platform architecture, or AI/ML architecture
- Strong hands-on experience with Generative AI, LLMs, ML systems, RAG architectures, vector databases, and AI application integration
- Proven experience in cloud architecture and solution design on at least one major cloud platform: AWS, Azure, or Google Cloud Platform (GCP)
- Strong understanding of cloud-native services including compute, storage, networking, identity and access management, security, and AI/ML services
- Expertise in API architecture, microservices, distributed systems, event-driven architecture, and system integration patterns
- Experience designing solutions with strong security, resiliency, scalability, observability, and performance considerations
- Working knowledge of AI governance, Responsible AI, model risk, compliance, testing, and operational controls
- Ability to lead architecture discussions and clearly communicate complex technical concepts to technical and business stakeholders
- Strong collaboration, problem-solving, and stakeholder management skills
- collaboration
- stakeholder management
- clear communication
- Generative AI
- LLMs
- RAG architectures
