AI Lead Architect

About Infinitive:
Infinitive is a data and AI consultancy that enables its clients to modernize monetize and operationalize their data to create lasting and substantial value. We possess deep industry and technology expertise to drive and sustain adoption of new capabilities. We match our people and personalities to our clients culture while bringing the right mix of talent and skills to enable high return on investment.

Infinitive has been named Best Small Firms to Work For by Consulting Magazine 9 times most recently in 2026. Infinitive has also been named a Washington Post Top Workplace Washington Business Journal Best Places to Work and Virginia Business Best Places to Work.

Infinitive is seeking a visionary and hands-on AI Architect to lead the architecture rollout and operational governance of our AI this pivotal role you will bridge modern cloud data architectures and generative/agentic AI tooling.

You will be responsible for defining how Infinitive and its clients accelerate software delivery data platform modernization and code migration using AI-assisted engineering. From configuring agentic workflows with Claude Code to establishing automated reconciliation test benches and measuring developer throughput you will set the engineering standards for the next era of delivery.

• Architect and Operate the AI Factory: Design build and continuously refine Infinitives enterprise AI Factory ecosystem enabling rapid legacy-to-modern code conversions and automated data engineering workflows.

• Claude Code & Agentic Workflows: Formulate system prompts structured project instructions rule sets and operational guardrails for developer tooling including Claude Code and related AI coding agents.

• Conversion Archetypes & Blueprints: Develop standardize and maintain modular conversion templates categorized by technical archetype (e.g. legacy ETL/SQL to modern PySpark on-prem warehouse models to lakehouse architectures).

• Automated Test & Reconciliation Harness: Architect robust automated validation frameworks and reconciliation test harnesses to verify data integrity schema consistency and business logic parity between legacy source implementations and AI-generated code.

• CI/CD & Automated Pattern Enforcement: Integrate automated static analysis linters and architectural pattern-checking pipelines directly into enterprise CI/CD workflows to catch regressions drift and anti-patterns prior to deployment.

• Hands-on Engineering: Write clean production-grade Python PySpark and advanced SQL for complex data pipelines lakehouse architectures and distributed computing tasks.

• Platform Optimization: Design and tune modern lakehouse solutions on Databricks ensuring adherence to performance security and cost-efficiency (FinOps) best practices.

• AI-Assisted Engineering Governance: Establish policies risk controls and quality gates governing code synthesis data security intellectual property safety and prompt governance.

• Productivity & Delivery Metrics: Define track and report quantitative metrics assessing engineering acceleration developer velocity cycle time reductions defect rates and ROI across AI Factory initiatives.

• Mentorship & Technical Leadership: Serve as a subject matter expert and coach to technical leads data engineers and consulting delivery teams adopting AI-assisted development tools.

• Education: Bachelors degree in Computer Science Information Systems Software Engineering or a related technical discipline.

• Certification: Databricks Certified (Databricks Certified Data Engineer Professional Solutions Architect or Machine Learning Professional strongly preferred).

• Architecture Experience: 7 years of progressive experience in data architecture software engineering or technical delivery with at least 2 years architecting or scaling modern AI/LLM-assisted engineering workflows.

• Hands-on Languages & Frameworks: Expert proficiency in Python PySpark and SQL.

• AI Tooling & Prompt Architecture: 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.

• Lakehouse & Cloud: Proven track record designing scalable architectures on Databricks alongside AWS or Azure environments.

• DevOps & Quality Automation: Strong background designing CI/CD pipelines (e.g. GitHub Actions GitLab CI Azure DevOps) with automated testing linting and data reconciliation suites.

• Consulting & Leadership: Exceptional communication skills with the ability to articulate AI governance frameworks architectural patterns and productivity impact metrics to executive stakeholders and technical teams alike.

• Experience architecting migration pipelines converting legacy data platforms (e.g. Netezza Teradata Oracle Informatica SSIS) to Databricks Lakehouse.

• Working knowledge of FinOps principles and token/compute cost attribution for large-scale AI workloads.
  
  
  Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set level experience relevant training and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $140000- $210000.
  
  Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability protected veteran status or any other characteristic protected by applicable federal state or local law.