Platform Fullstack AI Engineer
Palo Alto CA and Santa Clara CA - Locals are preferred as Client need IN PERSON Interview
Long term contract
Own end-to-end delivery of major platform initiatives—from architecture and design through deployment and post-launch optimization
Lead deep technical ownership of
Kubernetes environments , including cluster management, networking, operators, container lifecycle, and multi-tenant orchestration
Design and build
scalable, reliable distributed systems
and cloud-native infrastructure on AWS and/or GCP
Drive engineering excellence through
code quality, design reviews, automation, and CI/CD best practices
Collaborate cross-functionally with
Product, AI, and Security teams
to align technical solutions with business objectives
Mentor engineers and guide architectural decisions, trade-offs, and delivery approaches
Partner with leadership to shape
engineering strategy, roadmap planning, and platform evolution
Required Qualifications
6+ years of experience in software engineering, with a strong focus on
backend systems and infrastructure
Proficiency in
Python and/or Go , with a track record of delivering production-grade systems
Deep, hands-on experience with
Kubernetes , including building and operating clusters in production environments
Proven expertise in designing and managing
distributed systems at scale
Strong experience with
cloud platforms (AWS and/or GCP) , including compute, networking, storage, and IAM
Experience with
Infrastructure as Code (Terraform or similar)
and CI/CD pipelines
Familiarity with
applied AI tools and ecosystems , such as agent frameworks, AI gateways, or models like Claude and LiteLLM
Strong system design skills and architectural decision-making capability
Excellent communication and collaboration skills across engineering, product, and security teams
Preferred Qualifications
Experience with observability tools such as
Prometheus, Grafana, Datadog, and OpenTelemetry
Exposure to
multi-cloud or hybrid infrastructure environments
Knowledge of
API gateways, AI gateways, and policy frameworks
(e.g., ABAC, OPA)
Experience in
service mesh architectures
or platform-as-a-service design
Demonstrated ability to improve
engineering productivity and operational efficiency at scale