AI and Gen AI Architecture

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.