Native AI Engineer

Intellectsoft

Native AI Engineer developing AI capabilities for a remote-first software provider specializing in governance technology. Designing and architecting scalable solutions in AI, Azure, and cloud environments.

Posted 5/21/2026full-timeRemote • 🇺🇦 UkraineMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

ASP.NETAzureCloudJavaScript.NETReact

About the role

Key responsibilities & impact

AI Feature Development: Design, build, and deploy production-grade AI capabilities into our SaaS product, utilizing RAG pipelines, autonomous agentic tools, and Model Context Protocol (MCP).
Architectural Engineering: Architect and maintain highly scalable, reliable backend solutions using ASP.NET Core and F#, strictly adhering to functional programming principles and event-driven architectures.
Vector & Data Management: Implement and optimize vector databases to ensure ultra-low latency, highly accurate semantic search and contextual data retrieval.
Model Selection & Evaluation: Evaluate, benchmark, and integrate diverse LLMs and foundation models, matching their unique capabilities to specific product requirements for optimal cost, speed, and accuracy.
Cloud & AI Infrastructure: Orchestrate and manage secure, scalable workloads within the Azure ecosystem, specifically leveraging Azure AI deployments.

Requirements

What you’ll need

AI & Agentic Frameworks: Proven experience building AI features into production SaaS products, including Agentic tools, RAG pipelines, and Model Context Protocol (MCP).
Vector Infrastructure: Deep understanding of vector databases and semantic search optimization.
Backend Engineering: Strong proficiency in ASP.NET Core and F# (or a deep commitment to Functional Programming paradigms).
Architecture: Experience designing and maintaining scalable, event-driven architectures.
Cloud Ecosystem: Hands-on experience with Azure deployments, specifically leveraging Azure AI infrastructure.
Frontend Integration: Experience working with React.js to deliver seamless, intuitive AI-driven user experiences.
**Nice to have:**
Familiarity with benchmarking and evaluating different LLM providers and models' unique capabilities to optimize cost and latency.
Experience with advanced prompt engineering, fine-tuning workflows, or guardrail implementation.
Knowledge of modern CI/CD practices for AI/MLOps in an Azure environment.

Benefits

Comp & perks

Udemy courses of your choice
Team-buildings, events, marathons & charity activities to connect and recharge
Workshops, trainings, expert knowledge-sharing that keep you growing
Clear career path
Absence days for work-life balance
Flexible hours & work setup - work from any of listed locations and organize your day your way

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI feature developmentRAG pipelinesautonomous agentic toolsModel Context Protocol (MCP)ASP.NET CoreF#functional programmingevent-driven architecturevector databasessemantic search optimization