Applied AI Architect

Databricks

. Own the end-to-end AI/ML technical strategy for accounts, from discovery through production deployment and consumption growth .

Posted 11/6/2026full-timeRemote • Arizona • United StatesMid-LevelSenior💰 $180,000 - $247,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI/ML solutions architecture, including proficiency in Python, SQL, and cloud infrastructure on AWS, Azure, or GCP. Capable of leading technical discussions and driving platform adoption while serving as a trusted advisor to stakeholders.

Highest-signal resume keywords

AI/ML Solutions ArchitectureML EngineeringCloud Infrastructure (AWS, Azure, GCP)Python and SQL ProficiencyDatabricks Platform Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI EngineeringML EngineeringDistributed Data Systems ArchitectureStreaming ArchitecturesLakehouse PatternsFine-TuningDrift MonitoringLive CodingDebuggingSolution-Building

Soft Skills

Excellent Communication Skills

Tools & Technologies

LangChainHugging FaceOpenAI APIsVector DatabasesObservability Systems

Certifications & Qualifications

Databricks Certifications

Industry Keywords

Technical Pre-SalesProduction DeploymentsData GovernanceCompetitive Platform ExperienceCloud Provider Background

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Own the end-to-end AI/ML technical strategy for accounts, from discovery through production deployment and consumption growth
Lead complex architecture discussions and design scalable, production-grade AI/ML solutions
Work with Retrieval-Augmented Generation, tool calling, multi-agent orchestration, guardrails, AI evaluation, and observability systems
Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
Drive technical wins in competitive scenarios through custom-built solutions demonstrating Databricks differentiation
Develop and declare an emerging technical specialization and become a go-to resource for the Field Engineering team
Orchestrate DSAs, SAs, and partners to deliver comprehensive solutions
Influence product direction through structured feedback on customer requirements and competitive gaps

Requirements

What you’ll need

6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role
Experience in ML Engineering, including cloud infrastructure on AWS, Azure, or GCP for production ML applications and drift monitoring
Experience in AI Engineering with LLMs and agentic systems, vector databases, fine-tuning, AI guardrails, and frameworks such as LangChain, Hugging Face, or OpenAI APIs
Strong coding proficiency in Python and SQL, including live coding, debugging, and solution-building
Deep expertise in distributed data systems architecture, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
Proficiency on the Databricks Platform or demonstrated ability to achieve proficiency rapidly
Developing technical specialization in an area such as real-time/streaming, ML/AI, data governance, or migrations
Ability to lead architecture discussions with senior technical stakeholders, including whiteboarding, design reviews, and trade-off analysis
Experience with production deployments on AWS, Azure, or GCP, including infrastructure, security, and governance
Track record of driving platform adoption and consumption growth within accounts
Excellent communication skills for translating complex architectures into business value
Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience
Willingness to travel up to 30%
Databricks certifications, competitive platform experience, data/AI company or cloud provider background, and industry domain expertise are nice to have

Benefits

Comp & perks

Annual performance bonus eligibility
Equity eligibility
Comprehensive benefits and perks (region-specific details provided by Databricks)
Remote work