Principal Solution Architect

San Francisco, CA, US • Posted 18 days ago • Updated 15 days ago
Full Time
75% Travel Required
On-site
$120,000 - $140,000/yr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Artificial Intelligence
  • Data Engineering
  • Large Language Models (LLMs)
  • Machine Learning (ML)
  • Machine Learning Operations (ML Ops)
  • Vector Databases
  • Amazon Web Services
  • Cloud Computing
  • Spark
  • Snowflake
  • Databricks
  • LLM
  • MLOps
  • Machine Learning
  • Stakeholder Management
  • Solutioning

Summary

Role Overview

As a Principal Solution Architect, you will be the primary technical strategist for our most complex, high-stakes enterprise engagements. You will bridge the gap between sophisticated Data Engineering architectures and cutting-edge AI/ML applications to solve real-world business challenges. This is a high-impact role requiring a blend of deep technical hands-on-keyboard expertise and executive-level storytelling.

Key Responsibilities

  • Technical Discovery & Strategy: Lead deep-dive discovery sessions to uncover client pain points. Translate messy data landscapes into elegant, scalable AI/ML roadmaps.

  • Architectural Design: Design end-to-end data architectures—from ingestion and transformation (ETL/ELT) to model deployment (MLOps) and visualization.

  • Cross-Functional Leadership: Act as the voice of the customer for Product and Engineering teams to influence the product roadmap based on market feedback.

  • Trusted Advisor: Build long-term relationships with CTOs, CDOs, and Lead Data Scientists, guiding them through the complexities of AI governance, ethics, and scalability.

 

Requirements

Technical Requirements

  • Data Engineering (Mastery): 8+ years of experience with distributed systems (Spark, Flink), modern data stacks (Snowflake, Databricks), and orchestration tools (Airflow, dbt).

  • AI/ML Expertise: Proven experience deploying ML models into production. Deep understanding of the ML lifecycle (MLOps), vector databases (Pinecone, Milvus), and fine-tuning Large Language Models (LLMs).

  • Cloud Infrastructure: Expert-level proficiency in at least one major cloud provider (AWS, Azure, or Google Cloud Platform), specifically around data and AI services (e.g., SageMaker, Vertex AI).

  • Architecture: Experience designing microservices-based architectures and API integrations.

Travel Flexibility: Flexbilit of travelling to client sites. You thrive in face-to-face environments where high-touch technical strategy and relationship building are key to executing complex deals.

 

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: PTPcwAEMddfJ5Bf
  • Position Id: 8887010
  • Posted 18 days ago
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