About The Position

As a Software Engineer in the Ascensus AI Program, you will help turn modern LLM capabilities into reliable, observable, production-grade software used by real business teams every day. This is a mid-level software engineering role for someone who is strong in core engineering fundamentals and excited to build practical AI-powered systems.

Requirements

  • 3-7 years of professional software engineering experience.
  • Bachelor’s degree in Computer Science , Computer Information Systems, Business Information Systems, a related technical field, or equivalent practical experience.
  • Strong experience with one or more modern programming languages, such as: Python JavaScript / TypeScript SQL Similar modern development platforms
  • Experience building production applications, APIs, integrations, backend services, workflow logic, or similar software components.
  • Familiarity with LLM-powered systems, such as: RAG Chatbots Agent workflows Tool use Prompt engineering AI-enabled application development
  • Strong software engineering fundamentals, including: Clean code Source control Unit testing CI/CD Refactoring Design patterns Maintainability
  • Working experience with SQL for data inspection, analysis, troubleshooting, or integration.
  • Ability to read application logs, traces, and telemetry to investigate issues and identify root causes.
  • Strong problem-solving skills.
  • Clear communication skills with technical and non-technical audiences.
  • Comfort working in ambiguous, fast-moving environments.
  • Curiosity, ownership, and the ability to learn new technologies quickly.

Nice To Haves

  • Building or contributing to AI/LLM-based systems
  • RAG pipelines
  • Chatbots or conversational AI products
  • Agentic applications
  • Prompt strategies
  • Tool-calling workflows
  • Agent orchestration
  • Durable workflows or platforms such as Temporal
  • Model Context Protocol, function calling, or enterprise tool integrations
  • REST APIs, service-oriented architectures, or event-driven systems
  • Azure, Azure AI Foundry, Azure DevOps, or related Microsoft cloud tools
  • Salesforce or other enterprise platforms
  • Observability tools such as Langfuse , New Relic, OpenTelemetry , or similar platforms
  • AI-powered development tools such as Cursor, Claude Code, GitHub Copilot, or similar tools
  • Technical documentation, diagrams, decision records, or design notes
  • Working with quality engineers, SDETs, operations engineers, support teams, and product owners

Responsibilities

  • AI-powered applications and agents
  • Retrieval-augmented generation, or RAG, pipelines
  • Agent workflows and orchestration
  • Prompt strategies and tool integrations
  • Secure integrations with enterprise systems
  • Observability, testing, and production reliability
  • AI-assisted software development using tools such as Cursor, Claude Code, or similar platforms
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