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AI Architect

Washington, DC, US • Posted 1 day ago • Updated 1 day ago

Contract W2

No Travel Required

On-site

Depends on Experience

Fitment

Dice Job Match Score™

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Job Details

Skills

Artificial Intelligence
Data Architecture
Data Integration
Data Warehouse
Continuous Integration and Development
Machine Learning (ML)
Database
Generative Artificial Intelligence (AI)
Infrastructure Architecture
Machine Learning Operations (ML Ops)

Summary

Title: Senior AI Architect

Location: Washington, District Of Columbia (4 DAYS ONSITE)

Duration: Long Term

Senior AI Architect should have the following skills sets/experience.

Experience Level: 8–10+ years in software engineering or data architecture, with at least 4+ years specifically dedicated to AI/ML systems design and deployment in production environments.
Cost Management: Proven ability to manage and optimize the computing costs associated with running heavy AI workloads (e.g., token optimization, GPU allocation).
Communication & Leadership: Exceptional ability to translate complex AI capabilities and limitations to C-suite executives and non-technical stakeholders.
Database Knowledge: Familiarity with SQL and data warehousing concepts (e.g., Snowflake, BigQuery) for data pipeline orchestration.

Essential Job Functions & Required Skills:

Enterprise AI Strategy: Lead the transition of AI projects from localized Proof of Concepts (PoCs) to scalable, enterprise-wide production systems.
Technology Selection: Evaluate and select the appropriate AI technologies (e.g., Deep Learning, Natural Language Processing, Computer Vision, Generative AI) based on business requirements, cost, latency, and data privacy constraints.
Architecture Design: Architect end-to-end AI pipelines, including data ingestion, model training/fine-tuning, deployment, and monitoring.
MLOps & Infrastructure: Design and implement robust MLOps practices for continuous integration, continuous deployment (CI/CD), and continuous training (CT) of AI models to prevent model drift and degradation.
Data & Integration: Work closely with data engineers to design the data architecture required for advanced AI, including vector databases and complex RAG workflows.
AI Governance & Ethics: Establish guardrails for AI usage, ensuring models are fair, transparent, secure against adversarial attacks, and compliant with data privacy regulations (e.g., GDPR, CCPA).

Thanks

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10528519
Position Id: 8933966
Posted 1 day ago

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