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Specialist Solutions Architect – Azure Infrastructure & AI Platform

AI Summary
Databricks is seeking a senior Specialist Solutions Architect to advise enterprise customers on Azure-based Databricks infrastructure and AI platform deployments. The role combines cloud architecture, technical pre-sales, platform administration, and hands-on solution development for large-scale AI, GenAI, and distributed data workloads. Key responsibilities include designing secure Azure environments, automating infrastructure with IaC, leading architecture discussions, and coordinating cross-functional technical teams. Candidates need deep Azure networking, identity, security, observability, Python, SQL, and Databricks-related expertise, along with the ability to communicate business value to executive stakeholders. The position is remote in the United States and includes travel of up to 30%.
Remote from
USA
Salary
USD 180k–247,500 / yr
Employment
Full Time
Experience
Director
Published
Apply before
5 Dec 2026
Listing views
19
Application actions
1
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Opportunity details

About this role.

FEQ427R143

As an 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. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy.

This role can be remote.

The impact you will have

  • Guide strategic customers through the full lifecycle of Databricks on Azure, including platform administration, from initial architectural design to production deployment
  • Architect and scale compute/networking infrastructure designed specifically for AI workloads, enterprise LLM deployments, and high-performance GenAI applications built on Databricks
  • Serve as a subject matter expert in core areas such as Microsoft Azure infrastructure, infrastructure-as-code (IaC), cloud networking, and identity management
  • Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
  • Orchestrate cross-functional resources (DSAs, SAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
  • Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For

  • 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role
  • 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
  • Advanced expertise across the following areas:
    • Security & Identity: Azure security controls, platform/network/data security, encryption, vulnerability management, compliance, and identity protocols (Microsoft Entra ID / SCIM, OAuth, SAML, Federation)
    • Networking & Deployments: Azure enterprise networking (VNet peering, ExpressRoute, Private Link), network routing, performance optimization, and large-scale deployment management
    • Platform Administration: High availability, disaster recovery, cluster orchestration, observability (Azure Monitor, Log Analytics), and Azure cost management
    • Infrastructure Automation (InfraOps): Hands-on automation using IaC tools (e.g., Terraform, Bicep, ARM) to build, maintain, and scale complex Azure environments
  • Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
  • Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
  • 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)
  • Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
  • Track record of driving platform adoption and consumption growth within accounts
  • Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
  • Willingness to travel up to 30% as needed

Nice to Have

  • Databricks certifications (Data Engineer, ML, Platform)
  • Microsoft Azure certifications (Azure Solutions Architect Expert, Azure Data Engineer)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you’ll position against
  • Background in a data/AI company or cloud provider

Interview Process

Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Presentation → Reference Check

Pay Range Transparency

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 total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$180,000—$247,500 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer’s discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a highly senior, customer-facing architecture role requiring broad Azure infrastructure depth alongside AI/ML platform, distributed systems, coding, and pre-sales expertise. The candidate must independently solve complex enterprise problems and influence both technical and executive stakeholders.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$213,750
US market range (per year)$180k–$260k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a USD 180,000–247,500 range but does not explicitly state its cadence. Yearly compensation is inferred from the senior US-based full-time solutions architecture role and the scale of the stated range. The midpoint is USD 213,750 per year; an estimated US market range is USD 180,000–260,000 per year, excluding bonus, equity, and other benefits.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a secure Databricks deployment on Azure for an enterprise with strict network isolation requirements?

I would begin with the organization's security, compliance, connectivity, and data-residency requirements. I would propose a segmented VNet design using private connectivity such as Private Link, controlled routing, appropriate NSGs, and centralized identity through Microsoft Entra ID. I would then automate the environment through Terraform, apply least-privilege access controls, configure monitoring and audit logging, and validate the design with threat-model and operational reviews.

Describe how you would optimize infrastructure for a production GenAI workload on Databricks.

I would profile the workload across model size, latency targets, throughput, retrieval needs, and cost constraints. The architecture would include appropriately configured GPU capacity, autoscaling policies, resilient model-serving endpoints, vector retrieval, observability, and load testing. I would continuously evaluate utilization, inference performance, data access patterns, and cost to refine the deployment.

How do you explain an architecture trade-off to both engineers and executive stakeholders?

For engineers, I explain assumptions, constraints, implementation choices, risks, and measurable performance or security impacts. For executives, I translate the same decision into business outcomes such as time to value, operational risk, scalability, and total cost. I use a concise visual architecture and clearly state the recommendation, alternatives, and decision criteria.

What is your approach to deploying Azure infrastructure consistently across multiple environments?

I use infrastructure-as-code with reusable modules, version control, peer review, automated validation, and environment-specific configuration. A CI/CD pipeline applies policy checks, security scanning, plan reviews, and controlled promotion from development through production. This approach improves repeatability, auditability, disaster recovery readiness, and operational consistency.

How would you troubleshoot poor performance in a large-scale streaming pipeline running on Databricks?

I would first establish the performance baseline and inspect end-to-end metrics for ingestion, compute utilization, shuffle activity, storage throughput, network behavior, and streaming lag. I would identify bottlenecks in partitioning, state management, cluster sizing, data layout, and downstream sinks, then test targeted changes. After validating improvements under representative load, I would document the tuning decisions and add alerts for the relevant service-level indicators.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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