Urgent Req: AI Architect District Of Columbia ( Onsite ) (Washington, D.C.) 12+ Months...!!!

[Murali Krishna Tummala]

Urgent Req: AI Architect District Of Columbia ( Onsite ) (Washington, D.C.) 12+ Months...!!!

Position Title* AI Architect
Position Responsibilities
4 DAYS ONSITE
Senior AI Architect should have the following skills/experience.
 Need genuine experience and genuine visa and Linked in

Mail me Resume kri...@readpointe.com

    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).