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Senior Lead Principal Platform Engineer

CB Smart Recruit


Job Location:

Los Angeles, CA - USA

Yearly Salary: $ 200000 - 300000
Posted: 2 July 2026 (30+ days ago)
Application Deadline: 29 September 2026
Vacancies: 1 Vacancy

Job Summary

Location: West Hollywood / Los Angeles CA
Work Model: On-site (5 days per week)
Employment Type: Full-Time
Compensation: $200000$300000 USD (depending on experience and seniority) plus a competitive sign-on bonus.

Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this role.

About the Opportunity

Our client is a well-funded early-stage AI company building a next-generation intelligence platform for high-stakes real-world decision making.

The platform ingests and fuses data from satellite feeds autonomous sensors logistics networks enterprise systems and open-source intelligence (OSINT) to power production AI/ML workloads knowledge graphs and intelligent decision-making systems.

This is not a traditional SaaS DevOps or chatbot company. The engineering team is building production AI infrastructure where reliability scalability security and developer productivity are mission-critical.

Were looking for a Senior Lead or Principal Platform Engineer who enjoys building platformsnot simply maintaining them. Youll own the cloud infrastructure Kubernetes platform CI/CD and GitOps workflows infrastructure automation and internal developer platform that enables engineering teams to build and deploy production AI systems at scale.

This is a highly collaborative hands-on engineering role with significant ownership and influence over the platform architecture.

The Role

As a Platform Engineer youll design build and operate the infrastructure that powers complex AI/ML workloads while creating the internal tooling and platform capabilities that help software engineers move faster and more reliably.

The ideal candidate has a strong software engineering foundation deep cloud infrastructure expertise and experience owning production Kubernetes environments from design through day-to-day operations.

Key Responsibilities
Platform Engineering
  • Design build and operate scalable cloud infrastructure supporting production AI/ML workloads.
  • Own Kubernetes infrastructure including architecture networking security upgrades scaling and operational reliability.
  • Build and evolve an internal developer platform that improves engineering productivity and deployment velocity.
  • Develop self-service infrastructure and automation that enables engineering teams to ship software quickly and safely.
  • Continuously improve developer experience through platform engineering best practices.
Cloud Infrastructure & DevOps
  • Design and implement modern CI/CD and GitOps workflows for production environments.
  • Build reusable Infrastructure-as-Code solutions using Terraform and related tooling.
  • Architect highly available resilient and cost-efficient cloud infrastructure.
  • Drive adoption of containerization Kubernetes and cloud-native infrastructure across engineering teams.
  • Support AI-powered development workflows using tools such as Claude Code Cursor GitHub Copilot or similar technologies.
AI Infrastructure
  • Build and optimize infrastructure supporting GPU-accelerated machine learning workloads.
  • Improve GPU provisioning scheduling utilization and resource management.
  • Support scalable infrastructure for model training inference and AI services deployed in production.
  • Partner closely with AI engineers to optimize platform performance and reliability.
Reliability & Operations
  • Lead the investigation and resolution of complex production incidents across cloud infrastructure Kubernetes networking and applications.
  • Perform root-cause analysis and implement long-term improvements that increase reliability.
  • Build comprehensive monitoring alerting logging and observability solutions.
  • Drive platform reliability performance optimization and operational excellence.
Collaboration & Architecture
  • Partner with software engineers AI engineers security teams and technical leadership on platform architecture decisions.
  • Produce technical design documentation for major infrastructure initiatives.
  • Champion engineering best practices around automation scalability security testing and reliability.
  • Evaluate emerging technologies that improve infrastructure capabilities and developer productivity.
Required Qualifications
  • Bachelors degree in Computer Science Software Engineering Information Technology or a related technical discipline (Masters preferred).
  • 5 years of experience building and operating production cloud infrastructure Platform Engineering DevOps or Site Reliability Engineering (SRE) environments.
  • Strong software engineering foundation with experience building automation tooling services or developer platforms using Python Go Bash or similar languages.
  • Demonstrated ownership of production Kubernetes clusters including architecture networking upgrades scaling and operational support.
  • Hands-on experience designing and building Infrastructure-as-Code solutions using Terraform including authoring reusable modules.
  • Strong experience designing and building CI/CD and GitOps pipelinesnot simply maintaining existing pipelines.
  • Deep experience with Google Cloud Platform (GCP) and/or AWS.
  • Strong understanding of containerization technologies including Docker and Kubernetes.
  • Experience building and operating production-scale distributed systems.
  • Strong troubleshooting skills across cloud infrastructure Kubernetes networking and applications.
  • Experience with observability platforms such as Prometheus Grafana Datadog ELK or equivalent.
  • Excellent communication and collaboration skills.
Preferred Qualifications

Experience with one or more of the following is highly desirable:

  • AI/ML infrastructure and GPU-accelerated workloads.
  • NVIDIA GPU infrastructure and CUDA environments.
  • Internal developer platforms and self-service infrastructure.
  • GitOps methodologies.
  • AI-native development tools such as Claude Code Cursor GitHub Copilot or Codex.
  • Security-focused environments including DevSecOps practices.
  • Air-gapped sovereign or highly regulated deployment environments.
  • Defense aerospace government or other mission-critical industries.
  • FedRAMP ITAR CMMC or similar compliance frameworks.
  • Serverless architectures and distributed systems.
What Were Looking For

Successful candidates will demonstrate:

  • A platform engineering mindset with experience designing building and owning infrastructurenot simply maintaining existing environments.
  • A strong software engineering foundation and passion for automation.
  • Experience building platforms and internal tooling that improve developer productivity.
  • Excellent systems thinking across cloud infrastructure Kubernetes networking security and distributed systems.
  • A high level of ownership and comfort working in fast-moving environments with significant technical responsibility.
  • A pragmatic approach to balancing reliability scalability security and developer experience.
Compensation & Benefits
  • Base salary: $200000$300000 depending on experience and seniority.
  • Competitive sign-on bonus.
  • Comprehensive benefits package.
  • Opportunity to join a well-funded high-growth AI company at an early stage with significant technical ownership.
  • Long-term career growth with opportunities to take on broader platform and infrastructure leadership responsibilities as the organization continues to scale.
Why Join
  • Build production infrastructure powering real-world AI systemsnot internal IT or traditional enterprise DevOps.
  • Own the Kubernetes platform developer experience and cloud infrastructure that enables AI engineers to move faster.
  • Work alongside a highly technical engineering team solving challenging platform and infrastructure problems.
  • Support GPU-accelerated AI/ML workloads deployed in production.
  • Help shape the technical foundation of a rapidly growing AI company where engineering quality ownership and innovation are highly valued.

If youre passionate about Platform Engineering cloud infrastructure Kubernetes automation and building the systems that power next-generation AI applications wed love to hear from you.


  • Competitive base salary of $200000$300000 USD (depending on experience and seniority)
  • Competitive sign-on bonus
  • Comprehensive benefits package
  • Significant technical ownership
  • The opportunity to join a well-funded early-stage AI company building next-generation AI infrastructure.

Candidates located anywhere in the U.S. are encouraged to apply. The company offers a competitive sign-on bonus for successful hires. Please note that relocation assistance is not provided.