AI Engineer — RAG Pipelines & AI Infra

WISETEK PROVIDERS INC

Virginia (MN)

On-site

USD 120,000 - 190,000

Full time

14 days+
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Job summary

Wisetek Providers, Inc. is seeking an experienced AI Architect to design and implement AI solutions, including RAG pipelines, vector databases, and multi-LLM integration across Azure and other providers. The role focuses on building scalable AI infrastructure, data pipelines, and governance for enterprise applications.

Responsibilities include designing secure tool calls, RBAC scopes, and monitoring, while evaluating models for quality and cost. Strong CI/CD and security practices are required.

Qualifications

  • 4–6 years of experience in AI/ML consulting or solutions design.
  • Experience with RAG pipelines and vector databases.
  • Proficiency with multiple LLMs and AI infrastructure.
  • Experience with CI/CD, security and monitoring.

Responsibilities

  • Architect and implement AI solutions using RAG pipelines and vector databases.
  • Integrate and operate AI infrastructure across Azure and cloud providers.
  • Develop and manage data pipelines with ETL/ELT and data quality gates.
  • Build agentic AI solutions with multi-agent orchestration and governance.
  • Evaluate and optimize models for quality, latency, safety and cost.
  • Implement CI/CD with automated tests and security scans.

Skills

AI solution design
RAG pipelines
LLM integration
Data pipeline design
CI/CD and security

Tools

Azure AI
Azure OpenAI
Llama
Claude
Semantic Kernel
LangChain
AutoGen
Microsoft Agent Framework
Azure Data Factory
Azure Databricks
AWS EMR
MCP servers

Job description

Wisetek Providers, Inc. is seeking an experienced AI Architect to design and implement AI solutions, including RAG pipelines, vector databases, and multi-LLM integration across Azure and other providers. The role focuses on building scalable AI infrastructure, data pipelines, and governance for enterprise applications.

Responsibilities include designing secure tool calls, RBAC scopes, and monitoring, while evaluating models for quality and cost. Strong CI/CD and security practices are required.

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