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AI​/ML + Data Architect

Job in Torrance, Los Angeles County, California, 90504, USA
Listing for: Programmers.io
Full Time position
Listed on 2026-05-18
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Engineer, Cloud Computing
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation , design and deployment.

Key Responsibilities
  • AI/ML Strategy:
    Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs, Generative AI, and predictive analytics.
  • AWS Cloud Governance:
    Act as the lead architect for AWS environments, ensuring best practices in VPC design, serverless architectures (Lambda), and cost optimization (Fin Ops).
  • Data Mesh & Analytics:
    Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making.
  • AI Ethics & Security:
    Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM, Guard Duty) are strictly followed.
Required Skills
  • Cloud Platform:
    Proficiency in AWS Ecosystem (S3, Sage Maker, Redshift, Glue, Bedrock, and EKS).
  • Data Frameworks:
    Experience with Snowflake, Databricks, or Apache Spark for large-scale data processing.
  • AI Frameworks:
    Familiarity with PyTorch, Tensor Flow, or Lang Chain for integrating AI into enterprise workflows.
  • Automation:
    Strong background in IaC (Infrastructure as Code) using Terraform or AWS Cloud Formation.
Preferred Qualifications
  • AWS

    Certifications:

    Highly preferred (e.g., AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer).
  • Analytics Background:
    Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes.
  • AI Integration:
    Experience moving AI projects from "Proof of Concept" (PoC) to full-scale enterprise production.
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