Specialist Solutions Architect - AI Tooling & Platform Management

FEQ127R316
This role can be remote, but preference is given to candidates located in the job listing area who can travel up to 20% when needed.
As a Specialist Solutions Architect (SSA)—AI Tooling & System Management, you will build and manage the AI tooling stack and system infrastructure that empowers Field Engineering to deliver customer outcomes with higher velocity. These capabilities will be utilized by our Go-To-Market teams, including Solutions Architects and Account Executives, to accelerate technical demos, proofs of concept, and customer engagements.
You will bring consistency to our internal AI tooling stack, establish standards for AI-driven development practices, and scale these capabilities across the department. A critical aspect of this role is building the infrastructure that enables agent networks to perform with high quality and reliability—including context management systems, data integrations, and supporting tooling.
Additionally, you will develop internal applications and technical tools that enhance the overall lifecycle, track adoption metrics to measure impact, and partner with stakeholders to drive continuous improvement through intelligent automation and AI-augmented workflows.
The Impact You Will Have

Architect production-level AI tooling deployments that meet security, networking, and data integration requirements
Build and maintain internal AI tooling infrastructure for demos, learning, building POCs, and production workflows across platforms, including AI-assisted development environments, Databricks environments, and cloud-based tooling
Establish consistency in the AI tooling stack by defining standards, best practices, and reusable patterns that enable Field Engineering to build with AI efficiently and reliably at scale
Build context management infrastructure for agent networks, including vector databases, knowledge bases, and retrieval systems that ensure AI agents have access to the right information at the right time
Design and implement system integrations to bring data from enterprise sources into AI applications, ensuring secure, scalable, and reliable data flows
Develop internal applications to streamline Field Engineering workflows, improve demo and builder environments, and accelerate customer engagement velocity
Track adoption metrics and tooling effectiveness by instrumenting the AI tooling stack, building dashboards, and providing data-driven insights to leadership on adoption rates, productivity gains, and ROI
Manage AI tooling infrastructure and spend by overseeing cloud costs, monitoring consumption as teams scale, resolving capacity issues, and deploying automation to reduce operational overhead
Partner with Scale and Technical Enablement teams to develop documentation, AI-powered development patterns, and training materials
Support Solution Architects with custom proof of concept environments, AI tooling configurations, and technical guidance for customer engagements
What We Look For
5+ years experience in a technical role with expertise in the following:

Cloud Platforms & Architecture: Cloud-native architecture in AWS, Azure, or GCP; serverless architecture
AI Tooling: AI-assisted development platforms (Databricks AI Assistant, Claude Code, Cursor), prompt engineering, AI workflow automation
Context Management & Agent Networks: Vector databases, RAG (Retrieval Augmented Generation), embedding models, knowledge base systems, multi-agent orchestration
Application Development: Building internal tools and web applications with TypeScript/Node.js, Python, or similar modern stacks
Metrics & Analytics: Instrumentation and telemetry systems, dashboards, adoption tracking, measuring tool effectiveness, data visualization
System Integration & Data Pipelines: Designing integrations between enterprise systems, ETL processes, API design, data synchronization, event-driven architectures
Security & Platform Administration: Platform security, network security, data security, Gen AI & model security, encryption, vulnerability management, compliance, secure API integration, identity management, infrastructure management
Infrastructure Automation & DevOps: IaC tools (Terraform), CI/CD pipelines, GitOps workflows
Deep Specialty Expertise in at least one of the following:

Security — Securing AI development environments, managing identities, securing data pipelines for AI, and implementing security best practices for AI workflows
System Integrations & Application Deployment — Designing and implementing integrations between disparate systems to enable AI data flows. Deploying applications on cloud infrastructure using best practices in security, networking, and scalability.
Developer Experience & AI Tooling — Modern developer workflows, AI-assisted development, optimizing developer productivity through AI tooling
Additional Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent work experience
Hands-on experience with Python; proficiency in TypeScript/JavaScript highly desirable
Experience with modern web application frameworks (React, Next.js) and deployment patterns is a plus
Hands-on experience with AI platforms and AI workflow automation
2+ years experience with data technologies (Spark, Kafka, data pipelines) and modern application architectures
Experience building solutions on Databricks is a big plus
Ability to meet expectations for technical training and role-specific outcomes within 6 months of hire
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.
Zone 1 Pay Range
$180,000—$247,500 USD
Zone 2 Pay Range
$180,000—$247,500 USD
Zone 3 Pay Range
$180,000—$247,500 USD
Zone 4 Pay Range
$180,000—$247,500 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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, please visit https://www.mybenefitsnow.com/databricks.
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.