Native AI Engineer (IR-521)

Intellectsoft is a software development company delivering innovative solutions since 2007. They operate across North America, Latin America, the Nordic region, the UK, and Europe. They specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies. Their clients include Jaguar Motors, Universal Pictures, and Harley-Davidson. The client for this role is a rapidly scaling, remote-first software provider specializing in governance technology, serving leading European industrial groups, major media conglomerates, and energy giants, including several Tier-1 publicly traded corporations.

• Proven experience building AI features into production SaaS products, including Agentic tools, RAG pipelines, and Model Context Protocol (MCP).
• Deep understanding of vector databases and semantic search optimization.
• Strong proficiency in ASP.NET Core and F# or a deep commitment to Functional Programming paradigms.
• Experience designing and maintaining scalable, event-driven architectures.
• Hands-on experience with Azure deployments, specifically leveraging Azure AI infrastructure.
• 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.

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