Lead AI Architect

Infinitive

. Design, build, and continuously refine Infinitive’s enterprise AI Factory ecosystem .

Posted 11/4/2026full-timeRemote • United StatesSenior💰 $140,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-assisted engineering workflows, with a strong focus on data architecture, automated testing, and CI/CD pipeline integration. Proficient in Python, PySpark, and SQL, with a proven ability to mentor teams and communicate complex technical concepts effectively.

Highest-signal resume keywords

Python ProgrammingDatabricks ArchitectureCI/CD Pipeline DesignAI/LLM Workflow EngineeringData Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPySparkSQLData EngineeringAutomated TestingArchitectural PatternsData ValidationCode ConversionMetrics TrackingLegacy Data Migration

Soft Skills

Exceptional CommunicationMentoringStakeholder Engagement

Tools & Technologies

DatabricksGitHub ActionsGitLab CIAzure DevOpsClaude Code

Certifications & Qualifications

Databricks Certified Data Engineer ProfessionalDatabricks Certified Solutions ArchitectDatabricks Certified Machine Learning Professional

Industry Keywords

AI GovernanceData SecurityFinOps PrinciplesCloud EnvironmentsData Integrity

Tech Stack

Tools & technologies

AWSAzureInformaticaOraclePySparkPythonSQLSSIS

About the role

Key responsibilities & impact

Design, build, and continuously refine Infinitive’s enterprise AI Factory ecosystem
Enable rapid legacy-to-modern code conversions and automated data engineering workflows
Formulate system prompts, structured project instructions, rule sets, and operational guardrails for Claude Code and related AI coding agents
Develop, standardize, and maintain modular conversion templates for technical archetypes
Architect automated validation frameworks and reconciliation test harnesses to verify data integrity, schema consistency, and business logic parity
Integrate static analysis, linters, and architectural pattern-checking pipelines into enterprise CI/CD workflows
Write production-grade Python, PySpark, and advanced SQL for data pipelines, lakehouse architectures, and distributed computing tasks
Design and tune Databricks lakehouse solutions for performance, security, and cost efficiency
Establish policies, risk controls, and quality gates for code synthesis, data security, intellectual property safety, and prompt governance
Define, track, and report metrics for engineering acceleration, developer velocity, cycle time reductions, defect rates, and ROI
Mentor technical leads, data engineers, and consulting delivery teams adopting AI-assisted development tools

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related technical discipline
Databricks Certified certification strongly preferred (Databricks Certified Data Engineer Professional, Solutions Architect, or Machine Learning Professional)
7+ years of progressive experience in data architecture, software engineering, or technical delivery
At least 2+ years architecting or scaling modern AI/LLM-assisted engineering workflows
Expert proficiency in Python, PySpark, and SQL
Deep hands-on experience structuring repository instructions, system prompts, guardrails, and context windows for developer tools like Claude Code, GitHub Copilot, or similar agentic coding environments
Proven track record designing scalable architectures on Databricks alongside AWS or Azure environments
Strong background designing CI/CD pipelines with automated testing, linting, and data reconciliation suites
Experience with GitHub Actions, GitLab CI, or Azure DevOps
Exceptional communication skills and ability to articulate AI governance frameworks, architectural patterns, and productivity impact metrics to executive stakeholders and technical teams
Preferred: experience architecting migration pipelines converting legacy data platforms such as Netezza, Teradata, Oracle, Informatica, or SSIS to Databricks Lakehouse
Preferred: working knowledge of FinOps principles and token/compute cost attribution for large-scale AI workloads
Must be legally authorized to work in the US for any employer
Must be eligible to be hired by Infinitive as a full-time employee without requiring Infinitive visa sponsorship at any time during employment