Top Remote Infrastructure Engineer Jobs

Own and build Grow Therapy's data security infrastructure: automated data classification, field-level masking/tokenization, encryption and key management, secure data connectors to AI tooling, and access controls. Define a multi-year vision, implement pipelines and services, and partner across Data, Engineering, and Detection & Response to make secure-by-default the company standard.

Supports worldwide deployment and installation of servers, hardware, operating systems, applications, security patches, and Oracle database changes. Coordinates installation teams, site surveys, logistics, deployment schedules, refresh plans, technical documentation, project plans, and standard operating procedures. Performs hardware configuration management and emergency installation support while responding to special projects and deployment surges. Requires extensive international travel to customer facilities.

As an ML Infrastructure Engineer, you'll develop platforms and solutions for running ML jobs efficiently, establish CI/CD practices, and lead initiatives in technology alignment.

Own and evolve Elicit's multi-cloud infrastructure (AWS/GCP/Kubernetes) to scale single-tenant deployments, improve observability and incident response, drive security and compliance (SOC 2, NIST), optimize cost/capacity, and enhance developer CI/CD and deployment experience. Contribute to backend code where infra and application intersect.

The Staff Cloud Infrastructure Engineer is responsible for designing, automating, and managing cloud infrastructure using AWS and tools like Terraform. This role involves collaborating with engineering teams, ensuring security, and mentoring others, all while building reliable and scalable systems.

The Infrastructure Engineer is responsible for building and maintaining deployment automation, CI/CD pipelines, and ensuring the operational health of production deployments across federal environments, focusing on automation and compliance.

As a Database & Infrastructure Engineer, you will optimize PostgreSQL infrastructure, improve performance, build internal tools, and design data delivery pipelines for a large-scale application.

Design and implement a virtual access layer to enable remote use of a physical AI lab, building scalable, secure infrastructure to process 100,000+ documents/day with LLMs, optimize GPU/LLM throughput, provide customizable interfaces, implement authentication/access controls, and lead projects from design to production.

The role involves designing and advancing infrastructure for the engineering team, ensuring the reliability of Kubernetes clusters, automating operations, and building machine learning infrastructure.

Lead product vision and multi-year strategy for developer infrastructure across the code lifecycle. Own roadmap for CI/CD, release automation, testing, deployments, and production readiness; drive migrations to simplify systems, measure quality with scorecards, partner with Engineering/SRE/Security, and integrate emerging (AI) capabilities to improve developer velocity and reliability.

Design and execute AWS GovCloud migrations using the 7 Rs, plan migration waves, automate infrastructure with Terraform, ensure secure hybrid connectivity and Zero Trust controls, validate performance and operational readiness, and support modernization to container and cloud-native platforms.

Own and evolve the company’s infrastructure platform, including GCP, Kubernetes, Temporal, GPU systems, deployment tooling, CI/CD, developer environments, and reliability practices. Build AI training and inference infrastructure, manage cloud costs, enforce security boundaries, improve observability and incident response, and guide architecture. The role includes on-call responsibilities, technical mentoring, roadmap ownership, and partnering closely with engineering teams to improve how systems are developed and operated.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Build and operate highly scalable storage infrastructure supporting petabyte-scale imagery data. Responsibilities include developing backend services and APIs, managing object storage and metadata indexing, tuning Elasticsearch, improving disaster recovery, monitoring performance, responding to incidents, contributing to architecture and roadmaps, and advising engineers. The role requires strong production software engineering experience with Go or Python, cloud-native systems, relational and non-relational databases, and highly available services.

As a Site Reliability Engineer, you'll enhance system reliability, collaborate on production readiness, define SLIs/SLOs, and improve incident response.

Lead delivery for the Batch Infrastructure team: design, build, and operate reliable, scalable compute platforms for scheduled and on-demand batch workloads. Collaborate with product/design/analytics, define technical plans, ensure availability (monitoring/on-call), set code and design standards, and mentor engineers to improve delivery and quality.

Designs and builds scalable, reliable infrastructure systems across compute, networking, cloud orchestration, storage, and observability. Drives technical strategy, architecture, roadmaps, cross-team alignment, cost optimization, and secure-by-default practices. Requires extensive experience with coding, concurrent and distributed systems, cloud platforms, system-level tradeoffs, and infrastructure engineering.

Build and operate multicloud Kubernetes infrastructure and platform capabilities, including cloud foundations, networking, identity, cluster lifecycle, disconnected deployments, packaging, GitOps delivery, infrastructure as code, observability, upgrades, and incident response. Partner with engineering teams to provide reusable self-service infrastructure primitives across commercial, government, secure, classified, and disconnected environments.

Build and operate multicloud Kubernetes infrastructure and platform capabilities across commercial, government, classified, and disconnected environments. Responsibilities include cloud foundations, networking, identity, cluster lifecycle, packaging, GitOps delivery, infrastructure-as-code, policy enforcement, staged rollouts, observability, incident response, and backup/recovery. The engineer will also create self-service infrastructure primitives for internal engineering teams and support reliable fleet-scale deployments.

The Software Engineer, Infrastructure will design, build, and operate core platform services while ensuring reliability, security, and efficiency through collaboration with various teams and improving developer experience.

Lead design and operation of test infrastructure at scale: test orchestration, smart selection, parallel sharding, flaky-test detection, observability, SLOs, and on-call. Define technical strategy, drive cross-team projects, mentor engineers, and reduce test feedback time to accelerate engineering velocity.

Lead and operate Kubernetes-based infrastructure (EKS/Porter), design CI/CD pipelines, ensure zero-downtime and high availability, and build observability and incident response practices. Collaborate with BizOps and data teams to support a modern lakehouse data platform and optimize SQL and data pipelines for performance and cost.

Own reliability, monitoring, and incident response for AI infrastructure; build automation and CI/CD tooling; manage Kubernetes/Docker production workloads; partner with infrastructure, security, and compliance; improve observability and documentation; develop internal full‑stack tooling in Go or Python.

Senior SRE on the IT Operations team owning reliability, monitoring, and incident response for AI infrastructure. Build automation, CI/CD and Kubernetes tooling, improve observability and documentation, and develop internal full-stack tools using Go or Python. Partner with Infrastructure, Security, and Compliance to scale secure, resilient AI deployment pipelines.