Top Remote Systems Engineer Jobs

Lead Model Based Systems Engineering initiatives across programs, applying MBSE processes, SysML, UML, UAF, MagicDraw, and Cameo. Guide total MBSE development activities, develop modeling strategies, solve complex engineering problems, and collaborate with leadership and project teams. Contribute to training materials, engineering best practices, Agile-MBSE adoption, digital engineering solutions, and the transition to a cloud-based digital enterprise.

Design and optimize large-scale machine learning model-serving systems, including distributed infrastructure, load balancing, auto-scaling, batching, caching, and inference optimization. Build highly reliable, high-concurrency services serving billions of requests, improve latency and throughput, benchmark inference engines, and develop CI/CD infrastructure for model deployments. Partner with ML engineers to fine-tune and deploy open-source large language models.

Leads pre-sales technical support for HPE Networking solutions across the Atlanta metropolitan territory. Partners with sales teams, customers, and channel partners to qualify opportunities, design complex networking solutions, deliver presentations and demonstrations, build proofs of concept, prepare specifications, manage pipelines, and drive engagements through closure. The role focuses on campus and distributed branch networking, routing and switching, network security, NAC, wireless design, and consultative solution selling.

Leads pre-sales engineering for strategic enterprise accounts across Northern California. Partners with account managers to design and position networking solutions, deliver technical presentations, demonstrations, workshops, and proofs of concept, and develop proposals and architectures. Acts as a technical advisor throughout the sales cycle, supports demand generation, manages customer and partner relationships, tracks competitive networking trends, and helps opportunities progress through deployment and adoption.

Lead complex presales engagements for Boomi’s API Management solutions across North America. Design API-first strategies, governance models, security policies, developer portals, and enterprise architectures. Advise executive stakeholders on digital ecosystems and business value, lead proofs of concept and RFI/RFP responses, and demonstrate integration between API Management and iPaaS capabilities. The role requires deep expertise in API lifecycle management, gateways, identity and security frameworks, cloud platforms, microservices, service mesh, and event-driven architectures.

Lead systems engineering for a next-generation unmanned aircraft system. Responsibilities include defining system architecture, behaviors, requirements, interfaces, fault responses, and traceability; integrating avionics, autonomy, propulsion, sensors, and mission systems; conducting MBSE modeling, trade studies, safety analyses, flight testing, and performance validation; and coordinating cross-functional teams, DoD stakeholders, and government partners through development and operational deployment.

Design, build, and operate scalable hybrid human/machine data labeling platforms for autonomous vehicles. Own end-to-end projects, define platform roadmap, integrate ML-driven annotation, build high-performance UIs/APIs, and collaborate across ML, product, and operations to improve labeling quality and velocity.

Lead the technical direction for ML-powered search serving, including ranking, retrieval, inference pipelines, and serving infrastructure. Drive improvements in search quality, latency, cost, and reliability through experimentation and model optimization. Establish ML systems standards for evaluation, rollout safety, and observability; pursue advanced search initiatives; mentor senior engineers; and partner across search, ML platform, and product teams.

Lead the technical direction for Atlassian’s Search Serving platform, building globally scalable, low-latency agentic search systems. Own architecture for retrieval, indexing, query processing, and ML inference while improving quality, reliability, scalability, operability, and cost. Establish production ML practices for evaluation, experimentation, observability, rollouts, and incident response. Optimize inference for embedding, retrieval, and ranking models, and lead cross-team initiatives while mentoring senior engineers and aligning technical leaders.

As a Principal Machine Learning Systems Engineer, you will lead the development and implementation of machine learning systems and solutions to enhance team collaboration and productivity across Atlassian's software products.

Lead the technical direction of GenAI products and knowledge systems. Design and scale infrastructure for training, fine-tuning, serving language models and embeddings, and build retrieval, hybrid search, and RAG pipelines. Partner with applied scientists and engineering teams to rapidly prototype, productionize, and optimize reliable ML services. Establish best practices for deployment, monitoring, evaluation, latency, throughput, and resource efficiency.

Build and maintain lead-to-order business systems across Salesforce and connected platforms. Design complex applications, declarative automation, Apex and Lightning solutions, integrations, APIs, data models, and security controls. Remediate technical debt, lead migrations and tool rollouts, manage testing and cutovers, and ensure production systems are observable, documented, and governed. Partner cross-functionally to translate business requirements into scalable solutions while supporting AI capabilities in go-to-market workflows.

Architects, scales, and governs design systems, ensuring 1:1 parity between design assets and front-end code. Owns component libraries, design documentation, design tokens, accessibility standards, and UI pattern governance. Partners closely with development, product, and UX teams to guide implementation, manage component requests, conduct usability testing, reduce technical debt, and improve developer experience. Also maintains machine-readable documentation and AI-ready design infrastructure.

Build and operate full‑stack labeling tools and pipelines for autonomous vehicle ML. Design scalable UIs and services, integrate ML-driven annotation, create automation and QA tooling, own projects end‑to‑end, and collaborate with ML, Ops, Product, and Data teams to improve labeling quality and velocity.

Design, build, and operate scalable hybrid human/machine data-labeling tools and pipelines for autonomous vehicle ML. Implement full‑stack features (frontend, backend, APIs), integrate ML-driven annotation and active learning, build automation and QA tooling, and own projects end-to-end while collaborating with ML, product, and operations teams to improve labeling velocity and quality.

Own and improve Onebrief’s corporate security stack across endpoints, identity, SaaS, browsers, Zero Trust, EDR, SIEM, and MDM. Establish secure configuration baselines, detect and remediate drift, integrate telemetry, and build API-driven or infrastructure-as-code automation. Translate CMMC 2.0 and NIST-aligned requirements into continuously validated technical controls and reliable audit evidence. Partner with Corporate IT, Security Operations, GRC, and application owners to strengthen security posture and reduce manual compliance work.

Leads enterprise systems engineering across product lines, supporting product lifecycle practices, architecture reviews, modular design, requirements reuse, verification and validation, and design transfer. Partners with engineering teams to improve quality, reduce costs, standardize processes, and identify reuse opportunities. Pilots AI-enabled engineering improvements and promotes digital engineering, MBSE, automation, and continuous improvement across hardware, software, and integrated systems.

Provides technical leadership for enterprise infrastructure spanning compute, virtualization, storage, networking, Linux, Windows, Kubernetes, data centers, and AWS. Designs scalable platforms, leads infrastructure-as-code and automation initiatives, supports migrations, resolves complex incidents, and improves reliability, performance, and operational efficiency. The role mentors engineers, influences infrastructure strategy, participates in disaster recovery and on-call rotations, and evaluates AI-assisted and agent-based operational tooling.

Designs and maintains hardware/software systems across the system lifecycle. Develops software requirements specifications, defines system architectures and interfaces, performs MBSE in Cameo, supports formal qualification testing, and participates in technical reviews including SRR, PDR, CDR, and TRR. The role also produces engineering artifacts and supports requirements, architecture, interface, and test documentation.

Designs, develops, deploys, administers, and sustains MuleSoft Anypoint Platform and/or Informatica integrations in AWS GovCloud. Builds secure REST APIs and Mule applications, manages API gateways and lifecycle governance, implements authentication, monitoring, CI/CD, and data synchronization, and integrates Navy logistics and mission-partner systems. The role also performs testing, documentation, incident triage, performance tuning, RMF/STIG support, stakeholder coordination, and knowledge transfer.

Lead architecture, integration, deployment, security, and sustainment of the Informatica Data Governance Suite in AWS GovCloud. Design highly available and recoverable infrastructure, implement Infrastructure as Code and CI/CD, establish security and compliance controls, coordinate multidisciplinary engineering work, oversee testing and monitoring, manage technical risks, and transfer operational knowledge to NAVSUP personnel.

Leads solution architecture and engineering for a MuleSoft Anypoint Platform implementation in AWS GovCloud. Designs highly available, secure, recoverable infrastructure; establishes Infrastructure as Code, DevSecOps, CI/CD, monitoring, and configuration standards; guides API and data integration; and coordinates RMF/ATO, STIG compliance, testing, risk management, deployment, documentation, and production sustainment. Provides technical leadership, stakeholder coordination, Government briefings, and knowledge transfer to Navy personnel.

Implements, configures, deploys, and supports software platforms and HL7 interfaces. Troubleshoots operating systems, databases, VPN connectivity, and application integrations; manages customer support tickets, SLAs, documentation, and implementation timelines. Advises customers on technical requirements, collaborates across teams to improve reliability, and participates in an on-call rotation.

Design and build production AI applications for enterprise clients, including data processing, retrieval, APIs, tools, integrations, evaluations, and deployment. Partner with client experts to improve system performance and reliability, support cloud, CI/CD, security, and operational processes, and communicate technical tradeoffs clearly. The role also involves automating internal workflows and helping clients adopt new AI-enabled ways of working.

Designs, implements, manages, and tests technical infrastructure and systems solutions. Gathers and translates business requirements, develops architectural documentation and standards, coordinates vendors, reviews technical work, mentors engineers, troubleshoots complex systems, and ensures compliance with risk, regulatory, audit, and internal control requirements. The role also maintains expertise in banking applications, supported technologies, and industry best practices.