<p data-pm-slice="1 1 []">FEQ427R143</p> <p data-path-to-node="12"><span style="margin: 0px; padding: 0px;">As an<strong> </strong>Infrastructure & AI Platform Specialist Solutions Architect (SSA), you will serve as a trusted technical advisor, guiding enterprise customers through the architecture, cloud infrastructure, and AI deployment patterns of their Databricks Platform on Microsoft Azure. <span style="margin: 0px; padding: 0px;">You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy.</span></span></p> <p data-path-to-node="13">This role can be remote.</p> <p data-renderer-start-pos="2367"><strong data-renderer-mark="true">The impact you will have</strong></p> <ul> <li data-renderer-start-pos="2367">Guide strategic customers through the full lifecycle of Databricks on Azure, including platform administration, from initial architectural design to production deployment</li> <li data-renderer-start-pos="2367">Architect and scale compute/networking infrastructure designed specifically for AI workloads, enterprise LLM deployments, and high-performance GenAI applications built on Databricks</li> <li data-renderer-start-pos="2367">Serve as a subject matter expert in core areas such as Microsoft Azure infrastructure, infrastructure-as-code (IaC), cloud networking, and identity management</li> <li>Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions</li> <li>Orchestrate cross-functional resources (DSAs, SAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs</li> <li>Influence product direction by providing structured feedback on customer requirements and competitive gaps</li> </ul> <p><strong>What We Look For</strong></p> <ul> <li>6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role</li> <li>Hands-on experience architecting underlying cloud infrastructure for AI/ML execution—including accelerator configuration (GPUs/TPUs), scalable model serving infrastructure, vectorized data retrieval, and balancing cloud performance vs. cost for large-scale AI workloads</li> <li>Advanced expertise across the following areas: <ul> <li><span class="citation-945 citation-end-945">Security & Identit</span>y: Azure security controls, platform/network/data security, encryption, vulnerability management, compliance, and identity protocols (Microsoft Entra ID / SCIM, OAuth, SAML, Federation)</li> <li>Networking & Deployments: Azure enterprise networking (VNet peering, ExpressRoute, Private Link), network routing, performance optimization, and large-scale deployment management</li> <li>Platform Administration: High availability, disaster recovery, cluster orchestration, observability (Azure Monitor, Log Analytics), and Azure cost management</li> <li>Infrastructure Automation (InfraOps): Hands-on automation using IaC tools (e.g., Terraform, Bicep, ARM) to build, maintain, and scale complex Azure <span class="citation-944 citation-end-944">environments</span></li> </ul> </li> <li>Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills</li> <li>Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms</li> <li>Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)</li> <li>Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis</li> <li>Track record of driving platform adoption and consumption growth within accounts</li> <li>Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences</li> <li>Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)</li> <li>Willingness to travel up to 30% as needed</li> </ul> <p><strong>Nice to Have</strong></p> <ul> <li>Databricks certifications (Data Engineer, ML, Platform)</li> <li>Microsoft Azure certifications (Azure Solutions Architect Expert, Azure Data Engineer)</li> <li>Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against</li> <li>Background in a data/AI company or cloud provider</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p> </p> <p><strong>Pay Range Transparency</strong></p> <p><span style="font-weight: 400; font-size: 14px;">Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The