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soc-2 jobs in San Diego

$220,203 – $275,254 · Posted 7 days ago

Lead a team of cloud engineers building the nervous system for Brain Corp's fleet of 30,000+ autonomous mobile robots. Own the platform's reliability, roadmap, and architecture while managing team hiring, onboarding, and career development. Drive high-performance delivery across robot and customer-facing interfaces, balance competing priorities (performance, cost, reliability, scalability), and partner with principal and staff engineers on long-term platform strategy. Stay hands-on enough to make sound architectural decisions and earn senior engineer trust during a period of significant growth.

San DiegoLast seen 4 days ago
$220,203 – $275,254 · Posted 7 days ago

Lead a team of cloud engineers building the backend platform that powers Brain Corp's global fleet of 30,000+ autonomous mobile robots. Own the platform's reliability, roadmap, and architecture as it scales to support fleet operations and customer-facing applications. Balance hands-on technical leadership with people management—mentor engineers, drive hiring and onboarding, own production reliability and incident response, and partner with principal/staff engineers on distributed-systems architecture. Navigate tradeoffs between performance, cost, reliability, and scalability while shipping features that robots in the field depend on.

San DiegoLast seen 4 days ago
$187,363 – $265,900 · Posted 8 days ago

Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go. Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.

San DiegoLast seen 6 days ago
$121,625 – $217,711 · Posted 10 days ago

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams. Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

San DiegoLast seen 8 days ago
$125,000 – $160,000 · Posted 11 days ago

Own and evolve infrastructure, deployment systems, and cloud environments powering Clinically AI's healthcare AI platform. Design and maintain GCP infrastructure with focus on GKE, Kubernetes, and secure multi-environment deployments; build Infrastructure-as-Code using Terraform and Helm charts; optimize CI/CD pipelines with GitHub Actions; implement observability, security best practices, and incident response. Work closely with Backend, AI, and Product teams to support scalable infrastructure for services, AI pipelines, and high-throughput workloads.

San DiegoLast seen 9 days ago
$125,000 – $160,000 · Posted 12 days ago

Own and evolve the cloud infrastructure, deployment systems, and CI/CD pipelines powering Clinically AI's healthcare platform on GCP. Design and maintain cloud infrastructure using GKE, Terraform, and Helm; build reliable CI/CD pipelines with GitHub Actions; implement observability, security best practices, and incident response processes. Work closely with Backend, AI, and Product teams to support scalable infrastructure for AI pipelines, real-time processing, and multi-environment deployments. Operate with significant autonomy across cloud-native architecture while optimizing for performance, reliability, cost, and compliance.

San DiegoLast seen 10 days ago