What are the responsibilities and job description for the AI and Gen AI Architecture position at Value Technology Inc?
Job Title: AI and Gen AI Architecture
Location: Palo Alto/California (Hybrid)
Experience: 8-10 years
Job Summary
Value Technology is seeking an experienced and highly skilled AI & Gen AI Architect to lead the design, development, and deployment of scalable AI-driven platforms and cloud-native infrastructure solutions. The ideal candidate will have strong expertise in backend engineering, Kubernetes, distributed systems, cloud technologies, and applied Generative AI frameworks. This role requires hands-on technical leadership, architectural decision-making, and close collaboration with Product, AI, and Security teams to deliver innovative and reliable solutions.
Key Responsibilities:
- Own end-to-end delivery of major platform initiatives, from design through deployment and post-launch success.
- Own Kubernetes at depth — clusters, networking, operators, container lifecycle, and multi-tenant orchestration.
- Design, develop, and optimize distributed services and cloud-native infrastructure on AWS and/or Google Cloud Platform for scale, reliability, and performance.
- Drive engineering excellence through code quality standards, design reviews, automation, and CI/CD best practices.
- Collaborate across teams — Product, AI, and Security — to align architecture with business objectives.
- Be a mentor and multiplier, guiding engineers through architecture decisions, trade-offs, and delivery.
- Partner with leadership to align engineering strategy with product objectives and technical roadmap.
What We’re Looking For
- 6 years of software engineering with deep backend and infrastructure focus.
- Strong programming skills in Python and/or go — you ship production code, not just scripts and configs.
- Deep, hands-on Kubernetes experience — building and operating clusters, not just deploying to them.
- Proven experience designing and operating distributed systems in production.
- Cloud-native fluency across AWS and/or Google Cloud Platform — compute, storage, IAM, networking, and managed services.
- Experience with infrastructure-as-code (Terraform or similar) and CI/CD pipelines.
- Familiarity with applied AI tooling and patterns — agentic AI tools (Claude, LiteLLM), AI gateways, agent frameworks — and being able to build backend services that integrate with them.
- Strong system design and architectural judgment.
- Clear communicator who partners well across product, security, and AI teams.