Mindlance

Mindlance

AI Architect

Washington, District of Columbia, USA · third party, contract

Sponsorship not specifiedDetected 126 days ago
SQLBigQuerySnowflakeVector DatabasesCI/CDMachine LearningDeep LearningData ScienceNLPComputer VisionLLMsRAGMLOpsComplianceResearchLeadershipCommunication

About the role

  • This role bridges the gap between complex AI research and practical software engineering, orchestrating everything from traditional predictive models to advanced Generative AI and Retrieval-Augmented Generation (RAG) systems.
  • Database Knowledge: Familiarity with SQL and data warehousing concepts (e.g., Snowflake, BigQuery ) for data pipeline orchestration.

Responsibilities

  • 8 10+ years in software engineering or data architectur e, with at least 4+ years specifically dedicated to AI/ML systems design and deployment in production environments.
  • 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.
  • Experience Level: 8 10+ years in software engineering or data architectur e, with at least 4+ years specifically dedicated to AI/ML systems design and deployment in production environments.
  • 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.

Requirements

  • SKILLS / EXPERIENCE REQUIRED Senior AI Architect should have the following skills sets/experience.
  • Exceptional ability to translate complex AI capabilities and limitations to C-suite executives and non-technical stakeholders.
  • Familiarity with SQL and data warehousing concepts (e.g., Snowflake, BigQuery ) for data pipeline orchestration.
  • Work closely with data engineers to design the data architecture required for advanced AI, including vector databases and complex RAG workflows.
  • Communication & Leadership: Exceptional ability to translate complex AI capabilities and limitations to C-suite executives and non-technical stakeholders.
  • 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.
  • Data & Integration: Work closely with data engineers to design the data architecture required for advanced AI, including vector databases and complex RAG workflows.

Equal opportunity

  • Establish guardrails for AI usage, ensuring models are fair, transparent, secure against adversarial attacks, and compliant with data privacy regulations (e.g., GDPR, CCPA).
  • Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
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