Senior AI Software Engineer (.NET)

About the Position

We are seeking a Senior AI Software Engineer (.NET) to join our team in Yerevan, Armenia. You will play a pivotal role in developing and deploying AI-powered features in production services, transforming our logistics operations.

Problem Space

Logistics operations today are 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 modeled. That is where AI changes the game.

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.

Requirements

• 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

Nice to Have

• 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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