AI Software Engineer

Overview

Hybrid
$70 - $80
Contract - W2

Skills

API Management
C#
NoSQL
Microsoft Azure
Machine Learning (ML)
TypeScript
Artificial Intelligence

Job Details

As an AI Software Engineer, you will design and develop robust, cloud-native systems that power intelligent automation and decision-making. You will be a hands-on problem solver building APIs, Azure Functions, and event-driven services that form the backbone of scalable, AI-ready enterprise applications.

Responsibilities:

  • Design, build, and optimize APIs and Azure Function Apps to deliver performant, reliable, and secure cloud services.
  • Write clean, maintainable, and testable code in Python, C#, or TypeScript.

Integrate with databases (SQL, NoSQL, or cloud-native data stores) and design effective A/I software.

  • Data access patterns.
  • Implement event-driven architectures leveraging Azure Event Grid, Durable Functions, and API Management.
  • Rapidly prototype and experiment with new SDKs, APIs, and frameworks to support AI-driven and agentic workflows.
  • Develop monitoring, observability, and diagnostic tools to ensure reliability and performance.
  • Apply software engineering best practices, including automated testing, CI/CD, and cloud cost optimization.
  • Collaborate with peers through code reviews, technical design discussions, and mentorship.

Qualifications

  • 7 10+ years of professional software development experience in backend or full-stack engineering.
  • Proven ability as a hands-on problem solver who can translate complex requirements into reliable, maintainable solutions.
  • Proficiency in C#, or Python, with strong knowledge of object-oriented and functional programming principles.
  • Hands-on experience developing and deploying Azure Functions, APIs, and event-driven systems.
  • Experience integrating with databases and designing data interaction layers for performance and scalability.
  • Solid understanding of microservices, serverless architectures, and distributed systems.
  • Familiarity with Azure SDKs, Azure Cognitive Services, and cloud security best practices.
  • Strong communication and collaboration skills; thrives in agile, iterative development environments.
  • Practical exposure to AI/ML technologies, including LLMs, RAG, and orchestration tools like LangChain, AutoGen, or Semantic Kernel.
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