AI Engineer - #305549

Rapid Eagle Inc


Date: 5 hours ago
City: Minneapolis, MN
Salary: $60 - $70 per hour
Contract type: Full time
Benefits:

  • 401(k) matching
  • Dental insurance
  • Health insurance


AI Engineer

Onsite

Minneapolis MN

Skills:-

Context

  • Role spans AI engineering
  • Tech decisions influenced by broader product stack:
  • Frontend/backend for RAG and app work: Next.js and NestJS (Node)
  • Light work with data pipelines: Python; Snowflake as the data platform (medallion architecture: bronze/silver/gold)
  • Tools and AI coding assistants:
  • Claude Code
  • GitHub Copilot via Visual Studio
  • Evaluating vendor AI tools (e.g., Snowflake AI, Domo AI); use-case dependent.
  • MCP servers: discussed; on roadmap; not currently required for internal LLM routing/abstraction.


Must Have Requirements

  • Strong Python experience (production-grade software engineering).
  • Hands-on experience working with LLMs in production (general LLM best practices; not strictly RAG). Examples:
  • Efficient interaction patterns with LLMs (token management, sending full articles vs. selective context)
  • Agentic approaches for complex reasoning (e.g., applying AP style guide across thousands of rules)
  • Practical strategies to avoid context overload and maintain relevance.
  • Ability to “run with projects,” operate independently, and collaborate with stakeholders.
  • Minimum experience: approximately 5 years; must have “done it before.”


Should Have

  • Familiarity with Next.js/NestJS/Node for application/RAG-related work; strong Python candidates can ramp with AI coding tools.
  • CI/CD experience; Terraform not required (team strength exists, can learn on the job).
  • Good culture fit: collaborative, mission-driven, able to navigate flexible stack choices aligned with product teams.


Could Have:

  • Exposure to data engineering concepts and tooling:
  • Building ingestion/ETL/ELT pipelines (Python)
  • Working with Snowflake; experience in similar platforms (Redshift, Synapse) acceptable with ability to translate principles.
  • Familiarity with medallion architecture and data modeling concepts is helpful but not strictly required (team can support ramp-up).


Additional Notes

  • RAG work currently lives in Next/Nest (Node); none in Python at present.
  • Preference for principles over specific vendor experience; candidates with adjacent platform knowledge can adapt.

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