Top Remote Solutions Architect Jobs

Defines and governs enterprise architecture across applications, infrastructure, cloud, integrations, security, and data. Develops technology strategies and roadmaps, leads architecture governance and modernization initiatives, and guides cloud migration, application integration, infrastructure automation, resiliency, and security-by-design. Partners with executives, business stakeholders, product teams, engineers, cybersecurity teams, and vendors to align technology investments with business objectives. Mentors technical teams and communicates architectural decisions across technical and business audiences.

Develop technical solutions, mission architectures, proposals, and customer-facing demonstrations for drone detection and airspace technology. Lead solution planning for live flight events and trials, define system requirements and technical success criteria, and serve as a technical expert for government and enterprise customers. Collaborate across Sales, Marketing, Engineering, Product, and Program Management while supporting capture activities, customer discovery, proposal writing, and in-field testing. The role requires substantial domestic and international travel and eligibility for a U.S. security clearance.

Serve as a technical and product expert for institutional blockchain customers, supporting enterprise sales cycles through solution design, technical evaluations, demonstrations, and proof-of-value engagements. Advise financial institutions on Wallet, Nodes/APIs, and Staking products; translate business and technical needs into tailored architectures; collaborate with Product and Engineering; and represent the company at conferences and webinars. The role also develops technical documentation and incorporates customer feedback into product improvements.

Designs and delivers customer-focused solutions for ExtraHop’s cybersecurity and network visibility platform. Responsibilities include developing GUI tools, scripts, APIs, data visualizations, and automated workflows; analyzing network topologies and application stacks; performing root cause analysis; profiling applications; creating technical collateral; and training customer personnel. The role requires strong networking, application architecture, scripting, communication, and customer engagement skills.

Leads enterprise solution architecture across applications, infrastructure, data, integrations, and processes. Defines technology blueprints, architecture roadmaps, modernization strategies, governance standards, and transformation plans. Partners with executives, business leaders, product owners, and engineering teams to align technology investments with business objectives. Evaluates emerging technologies and vendors, guides complex programs, manages technical debt, develops business cases, and mentors architects while promoting architecture excellence.

Leads cloud, infrastructure, data, security, and AI architecture across AWS, Azure, Kubernetes, and infrastructure-as-code environments. Defines reference architectures, landing zones, data platforms, GenAI production patterns, security controls, cost models, and operational standards. Shapes client engagements, technical scope, and roadmaps; guides delivery through design reviews and mentoring. Requires hands-on production architecture experience, strong security and governance expertise, and the ability to operate effectively amid ambiguity.

Serve as the pre-sales technical expert for enterprise integrations, translating customer requirements into scoped integration blueprints, data flows, estimates, and implementation handoffs. Partner with sales, prospects, engineering, product, legal, and post-sales teams; conduct technical discovery, demos, and proof-of-concept integrations. Develop reusable integration patterns and architectures, assess feasibility and risk, and improve scoping processes based on delivery outcomes.

Designs, implements, and governs enterprise Salesforce solutions across Sales Cloud, Revenue Cloud, sales planning, and compensation management. Translates revenue and sales requirements into scalable architectures, defines data models and integrations, manages technical debt and release impact analysis, and supports an Oracle CX-to-Salesforce migration. Partners with business stakeholders, product owners, and delivery teams while applying hands-on expertise in Apex, LWC, Aura, Visualforce, Salesforce Flow, APIs, and middleware.

Designs, implements, and governs enterprise Oracle Fusion solutions across Finance and Supply Chain. Evaluates and replaces legacy Oracle EBS customizations with standard Fusion capabilities, architects integrations using OIC and APIs, leads EBS-to-Fusion transformation and data migration, and guides system integrators and implementation teams. The role also designs scalable architectures for future acquisitions, applies Fusion AI and RPA, and oversees reporting, security, analytics, and cloud extensions.

Lead technical strategy for named digital-native accounts, advising senior customer stakeholders on data, AI, streaming, and lakehouse architectures. Design production-grade solutions, drive Databricks adoption and consumption, lead technical demonstrations and competitive wins, coordinate cross-functional resources, and influence product direction. The role requires strong Python and SQL coding, public cloud deployment experience, distributed data systems expertise, and the ability to communicate complex architectures to technical and executive audiences.

Serve as the founding customer-facing engineer for Kimchi, leading demos, customer environment setup, LLM inference optimization, model routing, governance policy implementation, and serverless API integrations. Translate customer feedback into product improvements while identifying revenue expansion opportunities. Explain complex AI concepts to non-ML engineers and optimize workloads for coding, reasoning, and planning use cases.

Design and scale Kubernetes-native, GPU-accelerated cloud architectures for large-scale robotics simulation, synthetic data pipelines, training, and inference. Advise partners, optimize scheduling, storage, networking, and GPU utilization, and drive adoption of NVIDIA Physical AI frameworks while collaborating with product and engineering teams.

Lead Day 2 operations engagements with NVIDIA Cloud Partners: diagnose and fix production GPU/HPC/cloud issues, prototype and validate fixes, improve reliability, performance, and economics, and convert solutions into reusable procedures, automation, and feedback for product and engineering teams.

Partner with industry and account teams to design and deliver NVIDIA-based AI, HPC, and GPU/networking solutions for industrial robotics. Engage customers and partners, produce technical documentation and samples, support deployments both in datacenters and at the edge, and lead technical engagements with lighthouse customers and solution partners.

Lead Day 2 operations improvements across NVIDIA Cloud Partners operating GPU, HPC, and AI cloud infrastructure. Partner with engineering teams to troubleshoot production issues, improve reliability, performance, utilization, recovery, and economics, and prepare new NVIDIA technologies for operations. Raise operational maturity across tooling, telemetry, security, incident response, and automation. Convert validated solutions into procedures, architectures, assessments, and workflows while providing cross-partner feedback to NVIDIA engineering and product teams.

Design and deploy scalable AI inference architectures for strategic partners. Build and operate GPU inference recipes, optimize pipelines using leading inference backends, and guide disaggregated serving deployments. Evangelize Kubernetes, compute fabric, DevOps, and observability practices while mentoring customers and internal teams. Lead technical engagements, resolve complex infrastructure issues, create reference architectures, and provide product insights. The role also involves agent design, sandboxing, memory and retrieval systems, evaluation, skill governance, and model customization.

Designs and deploys large-scale AI and HPC GPU cloud infrastructure for NVIDIA Cloud Partners. Serves as the primary technical advisor across solution design, development, integration, production, debugging, and customer adoption. Builds proof-of-concepts, integrates AI software stacks, libraries, frameworks, and models, and delivers technical presentations and workshops. Partners with engineering, product, sales, and business teams to secure opportunities, guide product strategy, and support complex customer engagements throughout the lifecycle.

Build and scale robotics simulation and sim-to-real workflows for NVIDIA partners. Develop solutions involving robot rigging, physics, rendering, sensor simulation, synthetic data, GPU computing, and learned policies. Lead technical evaluations, proofs of concept, workshops, and reference implementations; diagnose performance and integration issues; validate hybrid physics and neural approaches; and collaborate with research, engineering, product, and customers to guide platform adoption and roadmaps.

Lead technical engagements with OEM and deployment partners to design, validate, and deploy scalable NVIDIA AI infrastructure. Map customer workloads to NVIDIA hardware and software, co-design architectures, resolve complex technical issues, drive platform adoption, and influence product priorities. Lead AI Factory build-readiness execution, deployment validation, technical enablement, and issue resolution across large-scale GPU infrastructure deployments. Travel up to 50% is required.

Designs and optimizes NVIDIA AI and HPC infrastructure for energy-sector customers, including GPU clusters, networking, storage, orchestration, monitoring, security, and edge deployments. Partners with customers and internal teams on architecture reviews, proof-of-concepts, benchmarks, production deployments, reference architectures, and technical documentation. Advises on distributed training, inference, RAG, cluster reliability, and performance optimization while supporting strategic customer and partner engagements.

Drive technical engagements for NVIDIA’s on-premises AI Factory solutions. Advise partners, OEMs, and enterprise customers; design and validate scalable architectures; support deployments and troubleshooting; enable adoption of NVIDIA platforms; and communicate customer needs to engineering and product teams. The role requires hands-on expertise across AI infrastructure, hardware, firmware, operating systems, cluster management, workload orchestration, and system integration.

Leads technical engagements with Tier-1 telecommunications customers and partners, mapping workloads to NVIDIA technologies. Designs scalable architectures, integration milestones, and deployment plans; validates solutions; troubleshoots complex issues; enables platform adoption; and communicates customer needs to engineering and product teams. The role requires deep telecom stack expertise, customer-facing technical leadership, and experience with software, hardware, AI inference, networking, containers, Kubernetes, and potentially CUDA/GPU programming.

Design secure, scalable AI and cloud architectures for strategic Microsoft partners. Lead architecture sessions, develop proofs of concept and pilots, provide technical implementation guidance, modernize legacy systems, and help partners build AI practices, reusable intellectual property, agentic solutions, and managed services. Collaborate with partner executives, architects, developers, and Microsoft engineering while integrating AI models with enterprise data, applications, APIs, security, governance, and observability.

Designs, implements, tests, and validates Ethernet networking solutions for AI-enabled data centers. Provides routing expertise across BGP, VXLAN, EVPN, Linux, CLOS architectures, and switch fabrics; develops automation scripts and deployment documentation; validates configurations in labs; collaborates with customers, engineering, and marketing; and supports network performance monitoring, technical presentations, and training.

Lead GPU and NVLink-based cluster design and validation for large-scale AI and HPC deployments. Advise cloud partners on architectures, perform performance modeling, debug deployment issues, support NPI rollouts, and relay field feedback to engineering.