Solution Architect, AI & Automation

Workforce Classification:

Telecommuter

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As a Solution Architect for AI & Automation
, you will design, implement, and support technical solutions for the Data Management, AI Engineering and Data Science teams, bridging the gap between technology and business requirement by working with engineering teams and customers to understand problems, customize products, provide technical solutions, and ensure successful integration, often focusing on software, cloud, or network infrastructure.

This is a remote/telecommuter position, working from home.

• Meet with clients to understand their technical challenges, goals, and requirements.
• Develop customized technical solutions, often involving software, data and AI, or cloud services to meet specific client needs.
• Act as a communication bridge between clients and internal engineering, development, and support teams.
• Create technical documentation, design documents, training materials, and proof of concepts for presentations.
• Drive clarity across stakeholders through consultation, creation, and discussion of architecture work products.
• Continually assess the value and effectiveness of work products within your discipline.
• Collaborate with enterprise and solution architects to define solution patterns and reference architectures.
• Workflow & Process Design:
  • Partner with business stakeholders to understand end‑to‑end processes, decisions, and information flows, and translate them into automated workflows.
  • Design workflow diagrams and process specifications that clearly define steps, inputs/outputs, and where human vs. automated vs. AI‑driven decisions occur.
• Data Substrate & Snowflake:
  • Collaborate with data and engineering teams to define the data required for each action or decision and curate it into a well‑modeled Snowflake “data substrate” (tables, views, and data contracts).
  • Work with data dictionaries/catalogs to ensure every workflow step has clear, reliable data sources and that changes to the data model are reflected in automations.
• AI‑Driven Automation:
  • Identify where AI capabilities (LLMs, classification, extraction, summarization, retrieval, etc.) can safely and effectively augment or replace manual work in workflows.
  • Specify requirements for custom AI agents (inputs, outputs, context, SLAs) and integrate those RESTful services as steps within workflow management tools in collaboration with the AI Engineering team.
• Systems Integration & Reliability:
  • Configure and maintain integrations between source systems, Snowflake, and other core systems via APIs and connectors, ensuring secure and reliable data flows.
  • Monitor and troubleshoot workflow runs, data issues, and AI‑agent calls; implement improvements to increase robustness, observability, and performance.
• Analytics, Feedback & Iteration:
  • Define and maintain metrics and dashboards to track workflow performance, throughput, and error rates using the underlying Snowflake data.
  • Gather feedback from users and stakeholders, run experiments, and iterate on workflow and agent designs to continuously improve business outcomes.

• Bachelor’s Degree in Engineering, Healthcare, Computer Science, or related field or (7) years of experience in an information technology or engineering position.
• (10) years of experience in data and systems design, architecture, and implementation…