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AI Architect

BitwiseUnited States🇺🇸United States

Why this role stands out

This remote AI Architect role at Bitwise offers you a unique opportunity to shape the future of AI-driven automation, leading innovative projects and developing cutting-edge agentic workflows. You'll thrive here if you have a strong background in data engineering and applied AI, with a passion for building LLM-powered applications and guiding delivery teams. Apply now to make a significant impact in a dynamic and forward-thinking tech company.

Quick overview

SeniorityMid Senior
Work modeRemote
LocationUnited States
GitApache SparkETLDatabricksLLMPythonGenerative AIPrompt EngineeringLangGraphRAG

Job description

Job Description
AI Architect - AI & Automation
Work Location: Remote
Key Responsibilities:
  • Own the technical roadmap for AI-driven data modeling, documentation generation, data quality rule generation, and transformation code generation.
  • Design agentic workflow architecture using frameworks such as LangGraph, CrewAI, or AutoGen.
  • Ensure all AI workflows operate within the client's AI governance and approval framework.
  • Lead a small delivery team (AI Tech Lead, AI Developer) through discovery, prioritization, and iterative delivery of automation solutions.
  • Act as the primary technical point of contact with client platform and data engineering stakeholders.
  • Required Qualifications 10+ years in data engineering or applied AI/ML, including 2+ years leading applied-AI delivery teams.
  • Proficiency on Databricks Platform Experience designing agentic or multi-step AI workflows (LangGraph, CrewAI, AutoGen, or equivalent).
  • Experience building LLM-powered applications, including prompt engineering, context engineering, and Retrieval-Augmented Generation (RAG).
  • Experience integrating large language models into data engineering pipelines within a governed enterprise environment.
  • Experience with LLM evaluation and human-in-the-loop validation workflows to ensure accuracy and reliability of AI-generated outputs; working knowledge of guardrails and responsible-AI practices.
  • Experience building reusable, modular GenAI components (e.g., plugins) using structured multi-agent patterns to enable repeatable automation.
  • Experience deploying, versioning, monitoring, and evaluating LLM solutions in production, including prompt/version management and feedback-loop mechanisms.
  • Strong understanding of ETL/ELT patterns, schema analysis, source-to-target mapping, data quality, data profiling and data modeling.
  • Experience in designing reusable framework integration patterns with Databricks Python, PySpark/Declarative pipelines
  • Understanding of Data Engineering frameworks such as Data Quality, Data Modelling, Metadata Enrichment, Sensitive data handling, STTM, Modular and testable Python or PySpark/Declarative pipeline code generation.
  • Experience in designing performance and cost optimized data engineering frameworks Client-facing consulting or delivery experience.
  • Experience leveraging Agentic coding platforms (for example, GitHub Copilot or Claude Code) effectively.
Preferred Qualifications:
Experience with Databricks AI/ML tooling.
Background in data quality automation or catalog/metadata generation.

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