Job Type: Contract
Contract Length: Ongoing
Pay Range: $75-$80/hr
Start Date: ASAP
Location: Hybrid - Palo Alto, CA
About the Opportunity:
Our client, a leader in Enterprise Cloud Data Management and AI Platforms, is looking for a skilled Senior Software Engineer - Enterprise AI to join their team for an Ongoing engagement. This project involves owning end-to-end delivery of major platform initiatives, focusing on scalable, reliable, and performant cloud-native infrastructure and deep Kubernetes orchestration to support next-generation enterprise AI tooling. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Platform Delivery: Own end-to-end delivery of major platform initiatives, from design through deployment and post-launch success.
- Kubernetes Ownership: Own Kubernetes at depth—managing clusters, networking, operators, container lifecycle, and multi-tenant orchestration.
- Cloud Development: Design, develop, and optimize distributed services and cloud-native infrastructure on AWS and/or GCP for scale, reliability, and performance.
- Engineering Excellence: Drive engineering excellence through code quality standards, design reviews, automation, and CI/CD best practices.
- Cross-Functional Collaboration: Collaborate across Product, AI, and Security teams to align architecture with strategic business objectives.
- Mentorship: Be a mentor and multiplier, guiding engineers through architecture decisions, trade-offs, and delivery.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 6+ years of software engineering with deep backend and infrastructure focus.
- Deep expertise in production programming using Python and/or Go. This isn't a learning role—you need to be a subject matter expert.
- Deep, hands-on experience building and operating distributed systems and Kubernetes clusters in production.
- Cloud-native fluency across AWS and/or GCP—including compute, storage, IAM, networking, and managed services.
- Experience with infrastructure-as-code (Terraform or similar) and established CI/CD pipelines.
- Familiarity with applied AI tooling and patterns, including agentic AI tools (Claude, LiteLLM), AI gateways, and agent frameworks, and integrating backend services with them.
- Strong system design and architectural judgment.
- Demonstrated ability to work autonomously and manage your own time effectively to meet project goals.
- Strong communication skills to partner well across product, security, and AI teams.
- W2 only (No C2C or 1099 contractors)





