Top Remote Platform Engineer Jobs

Designs, deploys, and supports technology platforms across complex production environments. Responsibilities include troubleshooting hardware and software issues, improving performance and reliability, establishing technical standards, evaluating technologies, managing code promotions, documenting solutions, analyzing requirements, and mentoring junior engineers. The role partners with business stakeholders to deliver scalable technical solutions and supports system administration, technical design, releases, and special projects.

Build and own backend services and APIs supporting money movement, payments, settlements, reconciliation, payroll integrations, retirement workflows, and financial compliance. Ship reliable production code, debug incidents, improve observability and operational tooling, and collaborate with product, compliance, operations, and engineering teams. Mentor engineers and ensure systems handling customer funds are correct, scalable, and well tested.

Build and maintain low-code solutions with Microsoft Power Platform, PowerApps, and Power Automate for federal modernization efforts. Support frontend and backend development, translate ambiguous requirements into working products, troubleshoot complex issues, participate in code reviews, and collaborate with product managers, designers, and stakeholders in a remote Agile environment.

Lead platform engineering strategy and architecture as the team’s senior individual contributor. Architect release infrastructure, GitOps pipelines, cloud-to-edge platforms, OS image lifecycles, supply-chain security, compliance automation, and internal AI tooling. Mentor engineers, author technical designs, conduct architecture reviews, plan roadmaps, and provide people management when needed. Ensure reliable delivery across cloud, airgapped, embedded, defense, and transportation environments.

Own the architecture, deployment, performance, and reliability of Stickerbox’s production machine learning pipeline. Optimize latency, cost, batching, caching, GPU utilization, model serving, and inference across image generation, speech recognition, and character models. Lead deployment strategies, capacity planning, observability, safety enforcement, automated quality checks, migrations, release engineering, and on-call operations for a global consumer hardware launch.

Own and scale the backend platform for Hapiko’s voice-activated sticker printer, including APIs, job queues, real-time device connections, cloud infrastructure, autoscaling, observability, cost instrumentation, release engineering, security, privacy, and on-call operations. The role requires production infrastructure ownership, experience scaling queue-driven or real-time systems, and strong Python and PostgreSQL skills, with Elixir experience or willingness to learn.

Develop and operate GoMining’s GCP-based cloud platform, including GKE, Kubernetes, Terraform, CI/CD, GitOps, observability, security, backups, and disaster recovery. Troubleshoot production incidents, improve reliability and performance, optimize costs, and support engineering teams with safe production delivery. Maintain infrastructure documentation and operational runbooks while collaborating with Engineering and Security teams.

Build and operate database and storage platform software, including services, APIs, developer tools, migrations, and lifecycle automation. Solve database scaling, performance, reliability, and availability problems across distributed systems, cloud infrastructure, and backend services. Partner with engineering teams on schemas and queries, lead technical projects, modernize platforms, participate in incident response, and use AI-assisted tools in development.

Build and operate database and storage platform software, including services, APIs, and developer tools for provisioning, migrations, upgrades, and lifecycle management. Solve scaling, performance, reliability, and data correctness challenges across databases, distributed systems, cloud infrastructure, and networking. Partner with engineering teams on schemas and platform adoption, lead technical projects through rollout, participate in on-call response, and use AI-assisted tools in development.

Design and deliver enterprise-scale AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Set architecture and optimization strategies for scalable, cost-efficient, responsible AI platforms. Lead model routing, caching, orchestration, and cloud deployments while mentoring engineers, influencing stakeholders, and advancing AI research into production.

Designs, configures, operates, and optimizes the enterprise ServiceNow platform. Responsibilities include developing workflows, integrations, automations, Agentic AI capabilities, and self-service tools; troubleshooting complex issues; supporting releases and incidents; conducting security and configuration audits; maintaining knowledge articles and SOPs; managing ticket queues, SLAs, Agile backlogs, and sprint priorities; and presenting platform metrics to IT management. Provides technical leadership, governance, mentoring, and long-term platform strategy.

Lead the architecture and development of enterprise AI platforms, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, safety, and transparency. Set long-term technical strategy, drive organization-wide standards, lead platform initiatives, partner cross-functionally, and mentor senior engineering and research leaders.

Lead the architecture, deployment, configuration, and sustainment of an Azure and Kubernetes-based Software Factory for the US Space Force. Manage DevSecOps tools, IaC and CI/CD pipelines, Linux infrastructure, security requirements, monitoring, patching, upgrades, and vulnerability remediation. Provide technical leadership, coach DevSecOps and application teams, onboard users, establish platform standards, and advance secure software delivery practices. Travel is required up to 25%.

Designs and owns shared test automation frameworks and scalable test execution infrastructure across web, mobile, and backend services. Builds tooling for test environments, test data, parallel execution, flaky-test detection, and infrastructure monitoring. Partners with engineering teams to improve test coverage and quality practices, reduces feedback-loop friction, and documents testing best practices. The role requires strong automation architecture, cloud-native infrastructure, cross-stack testing, and collaborative influence.

Build, operate, and evolve large-scale Kubernetes and cloud infrastructure. Responsibilities include platform reliability, production troubleshooting, automation, infrastructure as code, CI/CD, observability, incident response, disaster recovery, migrations, and technical leadership. The role requires autonomous ownership of complex infrastructure initiatives, production coding in Go, Python, or Java, and direct collaboration with technical stakeholders.

Architects and automates secure, scalable database platform provisioning, configuration, monitoring, remediation, and security. Troubleshoots complex database systems, establishes engineering and deployment standards, applies infrastructure as code and CI/CD practices, and collaborates with business and technology teams. The role supports cloud, containerized, SQL and NoSQL database environments, REST APIs, Kafka, and automated platform delivery.

Lead platform engineering across infrastructure, CI/CD, testing, developer tooling, observability, and secure software delivery. Build internal platforms, golden paths, and shared tooling that improve developer and AI-agent productivity. Establish engineering standards, integrate security controls into pipelines, shape repositories for coding agents, and measure impact through DORA metrics and engineering feedback.

Owns the Databricks platform across environments, including administration, architecture, identity and access, Unity Catalog, networking, security, governance, cost controls, automation, and CI/CD. Advises technical and business teams on scalable platform design, evaluates emerging Databricks capabilities, and partners with infrastructure and security teams. The role requires production Databricks expertise, Terraform proficiency, cloud networking knowledge, strong communication, and architectural judgment.

Leads the design, development, governance, and enterprise adoption of secure Generative AI platforms and applications. Responsibilities include architecting RAG and agent-based solutions, developing APIs and reusable frameworks, establishing evaluation and prompt engineering standards, ensuring security and responsible AI practices, mentoring engineers, influencing architecture, and driving technical strategy across teams.

Own and operate the production threat intelligence platform, maintaining system health, monitoring jobs, and ensuring data quality. Build intelligence-feed integrations, enrichment, tagging, and lifecycle workflows. Deliver intelligence to detections, blocklists, warehouses, and agent workflows. Partner with Security and Product stakeholders to translate requirements into technical capabilities, troubleshoot production issues, and implement durable fixes. Develop production-quality software using Python, Go, or Storm with CI/CD ownership, while responsibly applying generative AI.

Designs, develops, tests, deploys, and supports enterprise Microsoft Power Platform solutions for Department of the Interior programs. Builds Model-Driven Apps, Dataverse solutions, Power Pages sites, Power BI reports, and Power Automate workflows; integrates Microsoft 365, SharePoint, Azure, REST APIs, and external systems. Applies ALM, security, accessibility, governance, and data-quality practices while collaborating with federal stakeholders and Agile delivery teams. Provides production support, documentation, mentoring, performance optimization, and technical solution design.

Develop, test, deploy, and support Microsoft Power Platform solutions for federal programs. Build Model-Driven Apps, Dataverse configurations, Power Pages sites, Power BI reports, and Power Automate workflows. Integrate solutions with Microsoft 365, SharePoint, Azure, REST APIs, and external systems while following ALM, Agile, security, accessibility, privacy, and governance practices. Collaborate with stakeholders and delivery teams, troubleshoot production issues, document solutions, and contribute to reusable development practices.

Designs, operates, secures, and improves enterprise OpenShift and Kubernetes platforms across hybrid-cloud environments. Responsibilities include cluster lifecycle management, automation, troubleshooting, observability, resiliency, security controls, disaster recovery, developer self-service, incident response, documentation, and technical leadership. The engineer independently leads complex platform initiatives, collaborates across infrastructure and security teams, mentors engineers, and participates in on-call support.

Design and build a durable data storage platform that preserves source disagreements, provenance, uncertainty, historical versions, and evidence. Develop result and evidence stores, lineage tracking, versioned rules and configurations, reproducible decision records, and point-in-time entity views. Collaborate with entity-resolution and machine-learning teams to support probabilistic outputs. The role requires production data engineering experience, strong Python and SQL, PostgreSQL expertise, U.S. citizenship, and an active Secret clearance.

Own and operate core platform systems for hosted agent orchestration, including Beads Team Server, cloud-based Gas City, billing, permissions, and SSO. Design for distributed state, concurrency, reliability, observability, backups, security, and production failure recovery. Build primarily in Go across storage, runtimes, containers, and cloud infrastructure while collaborating closely with the CTO and startup team.