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Open nowPosted 31 days agoWe saw it 80 min after it went up

Senior AI Software Engineer (.NET)

Cargoo6 open roles

Where
Yerevan, Armenia
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Your applicationOpen nowSenior AI Software Engineer (.NET)Cargoo · Yerevan, Armenia

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The clock on this job

Early applications get read.

12.9% of postings close within 7 days. Measured by our own scanner across the market. Cargoo postings stay open a median of 29 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 12.9%7 days
  4. 21.0%14 days
  5. 35.6%30 days
  6. 58.5%60 days
This job: posted 31 days ago

Cargoo median: 29 days open

The posting

Problem Space

Logistics operations today are still largely:

  • manual
  • reactive
  • fragmented across tools
  • running on incomplete or late data
  • full of conflicting constraints
  • under real-time decision pressure
  • driven by evolving business rules
  • a mix of legacy and new systems

Much of this is unstructured: emails, documents, free-text updates, exceptions nobody modelled. That is where AI changes the game.

We’re building a system that:

  • ingests real-time operational data, structured and unstructured
  • supports planning and execution decisions, with AI agents that act where it’s safe and hand over to humans where it isn’t
  • adapts to constantly changing constraints

What You’ll Work On

  • AI in production. Building LLM- and agent-powered features into production .NET services: tool calling, structured outputs, retrieval over operational data, document and message understanding.
  • The seams. Designing the boundaries between deterministic business logic and probabilistic AI: validation, fallbacks, human-in-the-loop.
  • Trust. Making AI measurable and trustworthy: evals, test sets, observability, guardrails and cost/latency budgets.
  • Ownership. Owning features end to end, from problem framing with product to running them in production.

Design Principles

  • keep things simple before scalable
  • prefer explicit logic over magic abstractions, and that includes AI: deterministic where you can, model where you must
  • optimize for change, not perfection (models, prompts and providers will change)
  • measure AI behaviour, don’t trust vibes
  • avoid “framework-driven architecture”
  • accept that some parts will be ugly, temporarily

Tech Stack

.NET · Vue.js · service-oriented architecture · relational + operational data storage · cloud-based infrastructure · LLM APIs and agent tooling (e.g. Semantic Kernel / Microsoft.Extensions.AI, MCP) · vector/semantic search · eval and tracing tools

How We Build

  • AI-native development is the default. You use coding agents (e.g. Claude Code, Copilot) every day.
  • You own what you ship, whoever typed it: you review AI-generated code critically, test it and understand it.

What We Expect

  • Strong, senior-level .NET engineering
  • Ability to navigate uncertainty and work in ambiguity
  • Willingness to challenge decisions
  • Focus on outcomes, not just code
  • Understanding of trade-offs and complex systems, including when not to use AI
  • Preferring ownership over comfort

Strong Plus

  • Having shipped LLM/AI features to production and kept them running
  • Experience with evals, prompt/version management or AI observability
  • Python for prototyping and data work
  • Logistics or other real-time operations domain experience

What You Won’t Find Here

  • over-engineering everything upfront
  • unnecessary microservices
  • “clean architecture” for the sake of it
  • process-heavy development
  • AI demos that never reach production
  • wrapping a chatbot around a problem and calling it solved
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