Mindlance

Mindlance

AI Architect

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

Sponsorship not specifiedDetected 172 days ago
SQLBigQuerySnowflakeVector DatabasesCI/CDMachine LearningDeep LearningData ScienceNLPComputer VisionLLMsRAGMLOpsComplianceResearchLeadershipCommunication

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odds of building a lasting career here

40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 3 green-card filings in this occupation, 100% were for a worker who already held the job.

Third-party placement is common here

94% of this employer's visa filings place the worker at a client company rather than at the employer itself, across 14 clients. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: Wells Fargo · World Bank · Qualcomm

Files H-1B transfers

27 transfer filings in the last year, covering 27 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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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.
  • 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.

Responsibilities

  • 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.

Equal opportunity

  • 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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This listing is sourced directly from Mindlance's careers page and normalized into a canonical job model.