Top Solutions Architect Jobs

Lead technical architecture and delivery for enterprise customers by designing, configuring, and building Checkbox workflows, integrations, and custom functions. Lead implementations, workshops, demos, and proofs of concept; integrate APIs, SSO, and SCIM; create reusable technical patterns; and translate customer insights into product roadmap improvements. The role requires a hands-on, customer-facing technical professional experienced with B2B SaaS, enterprise deployments, systems thinking, and ambiguous environments.

Designs, builds, deploys, and optimizes production AI applications combining graph databases, knowledge graphs, LLMs, and orchestration frameworks. Advises strategic customers, translates business and data challenges into scalable architectures, leads stakeholder engagements, and ensures successful delivery. Develops production code, integrates customer systems, evaluates application performance, and shares expertise through workshops, training, documentation, and thought leadership. Requires deep expertise in enterprise architecture, cloud platforms, generative AI, data engineering, graph technologies, and stakeholder management.

Serve as a technical pre-sales advisor for GitLab’s AI-powered DevSecOps platform across Southern EMEA. Lead discovery, demonstrations, workshops, solution design, proofs of value, tenders, audits, and technical evaluations. Advise customers on software development, CI/CD, security, cloud, and digital transformation while partnering with Account Executives and internal teams to support revenue growth, platform adoption, and customer advocacy.

Lead customer and partner enablement for NVIDIA Embedded solutions from new product introduction through mass production. Define system requirements, architectures, specifications, documentation, and test plans. Collaborate with hardware, firmware, software, validation, sensor, AI, and project management teams to integrate solutions into automotive and robotic systems. Evaluate system performance, power efficiency, thermal and mechanical integration, and reliability while developing customer roadmaps and providing feedback for product improvements.

Serve as the senior technical contact for OEM Federal deployments of NVIDIA GPU-accelerated platforms. Own customer issues end to end, including troubleshooting, failure analysis, RMA procedures, root-cause investigation, and coordination with OEM support and NVIDIA engineering. Support secure Federal environments such as FedRAMP, IL5/IL6, and air-gapped SCIF facilities while maintaining sanitization and chain-of-custody requirements. Analyze multi-GPU systems, firmware, operating systems, networking, storage, and distributed workloads, with up to 35% travel.

Designs scalable AI, data, and technology solutions for finance by translating CFO organization needs into technical specifications and architectures. Partners with finance, IT, data, security, product, and engineering teams to address data flows, automation, ERP, compliance, and security requirements. Leads solution design, identifies technology gaps, guides project and workstream execution, and co-develops partner solutions that solve measurable business problems.

Leads technical engagements with VMware and ecosystem partners to design, validate, and deploy NVIDIA GPU-accelerated virtualization solutions. Maps customer workloads to NVIDIA technologies, supports vGPU, AI, data science, and visualization deployments, troubleshoots complex issues, drives platform adoption, and influences product roadmaps through customer feedback and cross-functional collaboration.

Leads NVIDIA’s OEM Solutions Architecture organization, coordinating technical teams through new product introduction, product integration, end-to-end solution development, and large-scale customer deployments. The role manages technical engagement priorities, resolves partner issues, aligns engineering and sales stakeholders, influences OEM strategy, and supports recruiting and team growth. It requires extensive OEM, data center deployment, solutions architecture management, cross-functional leadership, project management, and NVIDIA technology expertise.

Supports customer-facing technical engagements with OEM and deployment partners, helping design, validate, troubleshoot, and deploy scalable NVIDIA AI infrastructure solutions. The role contributes to architecture, integration plans, enablement programs, deployment guides, onboarding materials, documentation, and partner adoption while relaying technical feedback to engineering and product teams.

Leads cloud architecture and technical teams supporting federal IT modernization and national security missions. Designs, migrates, deploys, tests, and manages enterprise-scale solutions across AWS, Azure, and Google Cloud. Guides stakeholders, develops containerized applications using Kubernetes, applies DevOps and DevSecOps practices, and ensures security and compliance. Requires extensive cloud infrastructure experience, leadership capability, and eligibility for a Secret clearance.

Develop and deploy scalable AI, machine learning, deep learning, and data analytics solutions on cloud GPU platforms. Build customer proofs of concept using NVIDIA hardware and software, collaborate with cloud providers and sales teams, present technical solutions, support customer roadmaps, and resolve technical issues. Requires solutions or sales engineering experience, cloud deployment expertise, ML frameworks, GPUs, CUDA, DevOps/MLOps technologies, scripting, and strong communication skills.

Lead customer architecture and deployment of scalable AI inference systems across edge and cloud environments. Optimize speech, action, and synthetic data workflows for latency, throughput, memory usage, cost, and quality. Manage production inference configuration, monitoring, capacity planning, testing, releases, and troubleshooting. Evaluate model optimization techniques and create deployment recipes, demos, and enablement materials. Partner with customers, product teams, and engineering to guide technical decisions and accelerate adoption of NVIDIA technologies.

Leads the technical strategy and architecture for semiconductor wafer, package, and qualification testing. Defines test methodologies across ATE platforms, drives DFT and testability decisions, improves yield and test efficiency, and applies AI/ML to test analytics. Establishes roadmaps and technical standards, partners with engineering and manufacturing teams across sites, engages vendors and industry groups, and mentors senior test engineers.

Partner with engineering, product, and sales to design and deliver GPU-accelerated ML/HPC solutions for capital markets. Lead POCs, profile and optimize ML/DL models on NVIDIA GPUs, collaborate with client researchers to deploy models at scale on cloud or on-prem HPC, and produce technical collateral (notebooks, blogs) to drive adoption.

Architect and demonstrate simulation workflows using DSX Sim and Omniverse libraries to help partners and customers build, validate, optimize, and operationalize AI factory digital twins. Drive integration of Omniverse libraries, develop reference architectures, prototypes, benchmarks, and sample workflows, and coordinate with sales, product engineering, and partners to resolve blockers and advance adoption.

Designs scalable enterprise SaaS solutions, translates customer needs into technical requirements and implementation plans, develops architecture diagrams and Statements of Work, and advises customers throughout the sales-to-deployment lifecycle. Connects field insights with Product and Engineering roadmap decisions, improves solutioning processes, identifies implementation risks, mentors pre-sales and professional services teams, and strengthens reusable frameworks, integration patterns, and delivery practices.

Designs Salesforce-centered solutions spanning QGenda, Workday, MuleSoft, and integrated enterprise systems. Translates business requirements into functional designs, user stories, architecture artifacts, data mappings, and integration specifications. Leads design governance, root-cause analysis, feasibility discussions, backlog refinement, test scenario definition, and delivery support. Partners with Product, Engineering, QA, security, compliance, and SOX stakeholders while maintaining platform standards and identifying automation and simplification opportunities.

Leads client discovery and designs architectures for web, mobile, and AI products. Defines scopes, integrations, data models, cloud deployments, security, privacy, multi-tenant systems, and AI/RAG features. Reviews code and technical approaches, guides engineers, manages technical risks, and owns architecture quality through delivery. Requires strong client communication, software engineering experience, cloud expertise, integration design, production AI architecture, and agency or consultancy experience.

Lead client discovery and design architectures for web, mobile, and AI products. Define scopes, data models, integrations, cloud infrastructure, security, privacy, multi-tenant systems, and AI/LLM capabilities. Review code and technical approaches, guide engineers, manage technical risks, and maintain architecture documentation through delivery. The role requires client-facing communication, strong backend and cloud fundamentals, production architecture experience, and the ability to translate technical trade-offs into clear plans.

Designs and leads scalable, secure enterprise software solutions aligned with business strategy. Responsibilities include architecture roadmaps, application integration, modernization, architecture reviews, technical leadership, development standards, cloud and DevOps collaboration, vendor integration, and technical escalation support.

Own and support the XaitCPQ platform used for professional services scoping, pricing, proposals, and change requests. Investigate issues, triage bugs, configure workflows, coordinate with stakeholders and vendors, create documentation and training materials, support onboarding, and identify process improvements. The role requires strong communication, technical problem-solving, attention to detail, and familiarity with presales, professional services, platform administration, APIs, scripting, or related IT functions.

Designs secure, scalable, interoperable infrastructure solutions across cloud and on-premises environments. Translates business requirements into technical architectures, evaluates technology options, and guides implementation while aligning with enterprise standards. Collaborates with infrastructure, cloud, application, security, data, and architecture teams. The role requires hands-on experience with major cloud platforms, containerization, programming languages, DevOps tools, databases, IAM, data protection, and Agile practices.

Leads enterprise architecture across data, analytics, AI/ML, Generative AI, cloud platforms, integration, and automation. Defines target-state architectures, technology roadmaps, governance standards, and architecture guardrails; evaluates platforms and vendors; guides modernization and cloud transformation; and advises senior leadership. Partners across business, engineering, cybersecurity, and infrastructure teams to deliver scalable solutions involving AI platforms, agent frameworks, RAG, knowledge platforms, APIs, and event-driven architectures. Mentors technical teams and drives responsible AI, security, privacy, and data governance.

Represent 3M in optical interconnect standards organizations, lead technical contributions and specifications, translate standards and ecosystem trends into product strategy, build partnerships with hyperscale customers and vendors, and develop demonstrations supporting technical marketing. The role requires expertise in optical interconnect, co-packaged optics, data center connectivity, industry standards, and related optical technologies. It is remote in the US with travel of up to 30%.

Owns integration architecture for a global banking data governance program, connecting Collibra, Databricks, Azure, IBM BAW, and enterprise applications. Designs secure APIs, full-stack Java and Python services, network and secrets architecture, Kubernetes deployments, and CI/CD observability patterns. Leads hands-on troubleshooting across applications, APIs, batch jobs, containers, networks, and data stores while providing technical direction to engineering teams.