1,558 Platform Engineer jobs available for remote work from home. Apply for positions such as Senior Full Stack Engineer, Agentic AI Platform, Senior Product Engineer (Darkplane, Agentic Platform), Senior Platform & Reliability Engineer (all genders) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Lead the architecture, development, and operation of Lumina, CVS Health’s enterprise agentic AI platform, including its agents, retrieval systems, integrations, services, and user experiences. Guide platform reliability, security, governance, and engineering practices while coaching engineers and data scientists and partnering with product, security, compliance, and engineering teams.
You will build and evolve the Darkplane platform by working with TypeScript, Node.js, and Go to support agentic workflows and reliable AI-driven software development. Additionally, you will partner with AI engineers to design secure code execution environments and engage with customers to shape the product roadmap.
You will take architectural ownership of shared infrastructure services, including API gateways, persistent storage, and identity infrastructure. Additionally, you will design and establish on-call processes and mature observability practices across the platform.
You will lead the development of the JavaScript platform, defining interfaces and building automation to streamline software delivery across Netflix. This role involves owning core application development workflows, CI/CD pipelines, and developer tooling to enhance the daily experience of engineers.
You will design and deliver features for the Polyant AI agent platform, managing everything from data models and APIs to user interfaces and deployment pipelines. Additionally, you will develop agent capabilities such as tool execution, memory, and retrieval while ensuring platform reliability and security.
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You will design, build, and maintain scalable AWS infrastructure and Kubernetes clusters to support machine learning workflows. Additionally, you will develop internal developer tools and enhance platform observability, security, and CI/CD pipelines.
You will own the technological backbone of the company, managing AWS infrastructure, security, and compliance posture. Additionally, you will partner with the Operations team to automate internal IT processes and support the scaling of AI-native product features.
Design, build, and maintain system integrations across the technology environment using APIs, webhooks, and iPaaS platforms. Develop cloud infrastructure on Azure and contribute to technical design while applying AI tools to improve development workflows.
You will build and deploy production-grade LLM agents by integrating client data, tools, and context graphs within the Gemini Enterprise platform. The role involves pairing with client engineers to ensure successful adoption and long-term maintainability of the deployed solutions.
Design, develop, and maintain scalable backend services, APIs, and platform capabilities using Golang. Build and maintain platform tooling and shared primitives to support other engineering teams.
The engineer will own the global Kubernetes cluster footprint, internal CI/CD build platforms, and shared infrastructure services. They are responsible for designing reusable Terraform modules, managing observability standards, and ensuring disaster recovery for the platform.
You will design and operate the data management and annotation infrastructure to support the development of proprietary large-scale LLMs and VLM technologies. This includes building data pipelines, managing annotation workflows, and collaborating with AI researchers to improve model accuracy.
You will partner with cross-functional teams to define and implement a state-of-the-art AV data introspection software roadmap. Additionally, you will drive technical discussions and evangelize solutions to address gaps in existing tools and accelerate product development.
You will design and build core platform APIs for security data retrieval, risk scoring, and entity resolution while managing asynchronous data pipelines. Additionally, you will own platform workstreams from scoping through delivery and collaborate with cross-functional teams to integrate security data sources.
Lead security initiatives across products, cloud platforms, and GPU infrastructure by performing threat modeling, vulnerability assessments, and architecture reviews. Coordinate remediation efforts with engineering teams and establish security standards to reduce systemic risks.
The engineer will collaborate with cross-functional teams to build and scale payment platform components and next-gen payment capabilities. They will also diagnose production issues and advocate for engineering best practices including scalability and security.
Design, build, and operate cloud infrastructure and CI/CD automation to support a major federal HCM modernization program. Orchestrate quarterly Oracle cloud updates and maintain configuration baselines aligned with NIST standards.
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Design, build, and maintain CI/CD pipelines and cloud infrastructure for Oracle Fusion Cloud HCM within a FedRAMP-authorized environment. Orchestrate quarterly SaaS updates, manage disaster recovery capabilities, and ensure compliance with federal security standards.
The Software Engineer III will build and maintain developer platform tooling, AI capabilities, and reusable infrastructure components. This role involves working within product engineering teams to implement patterns, document systems, and facilitate AI-focused technical workshops.
![Software Mind is hiring for remote [VMT] Platform AI Software Engineer](/assets/2083550c-5c59-4fae-b76e-a23e4817e5f2.jpeg){kind=small}
You will own the trust layer of an AI agent for industrial plants, focusing on reliability, grounding, and performance. This involves diagnosing agent misbehavior, building evaluation harnesses, and implementing mechanisms to ensure output quality and accuracy.
You will design, deploy, and maintain production Kubernetes clusters while ensuring system reliability, observability, and security. Additionally, you will build automated CI/CD pipelines and optimize infrastructure performance, including CDN and edge configurations.
You will build and operate foundational systems, including continuous integration infrastructure and Kubernetes-based ephemeral environments, to enable efficient software development. Additionally, you will develop reusable APIs and automation tools to improve developer productivity and platform reliability across the organization.
The Staff Engineer will serve as the technical owner of the FHIR server platform, overseeing its architecture, performance, security, and cost-efficiency. They will drive FHIR standards conformance, implement access controls, and mentor engineering teams to ensure a scalable and reliable health data infrastructure.
You will build and maintain developer-facing surfaces and integrations that connect Elastic to the broader AI ecosystem, including language clients and CLI tools. You will also collaborate with product teams and external partners to design and deliver scalable infrastructure for agentic tools.
You will lead the design and operation of real-time voice AI systems while setting the technical strategy for the AI Agent Platform team. You will also mentor engineers and drive engineering excellence across reliability, security, and performance standards.
You will architect, build, and scale the infrastructure orchestration and distributed compute platform for decentralized model training. This includes managing multi-cloud deployments, ensuring fault-tolerant distributed ML systems, and handling real-world network conditions.
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The engineer will build and ship features for the Champion platform while supporting Applied AI teams in deploying and operating agentic solutions. They will also design and develop custom agents for specific business use cases using an AI-native development workflow.
The engineer will build and maintain features for the Champion AI platform while supporting Applied AI teams in deploying agentic solutions. Responsibilities include developing agent infrastructure, improving developer tooling, and directly creating production-ready agents for business use cases.
You will set the technical direction for the Serverless control plane and lead multi-quarter projects that orchestrate and manage services across cloud providers. Additionally, you will mentor engineers, improve system reliability, and participate in on-call rotations to ensure high operational standards.
Design and build scalable infrastructure for machine learning model training, fine-tuning, and evaluation workflows. Optimize distributed training systems for performance, cost-effectiveness, and ease of use for ML practitioners.
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