About The Position

We are hiring senior engineers who build fast, think AI-first, and can take agentic AI from prototype to production. You will design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication. You will work primarily in Python for AI services and integrate with our enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure), delivering trustworthy, cost-efficient, low-latency experiences in real customer workflows.

Requirements

  • Senior engineers who build fast, think AI-first
  • Can take agentic AI from prototype to production
  • Design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication
  • Primarily work in Python for AI services
  • Integrate with enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure)
  • Deliver trustworthy, cost-efficient, low-latency experiences in real customer workflows
  • Python (FastAPI, asyncio)
  • Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.
  • Memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.
  • Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.
  • Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.
  • AI-native backend services with evaluation harnesses, observability, and cost/latency/quality dashboards.
  • Embed AI features into the Speria stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.
  • AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.
  • Safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.
  • Full cycle agentic engineering: design → model/tool selection → API & UI → deployment → monitoring → continuous improvement.

Responsibilities

  • Build agentic AI applications on Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.
  • Design memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.
  • Integrate via Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.
  • Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.
  • Develop AI-native backend services in Python (FastAPI, asyncio) with evaluation harnesses, observability, and cost/latency/quality dashboards.
  • Embed AI features into the Speria stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.
  • Use AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.
  • Implement safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.
  • Implement full cycle agentic engineering: design → model/tool selection → API & UI → deployment → monitoring → continuous improvement.
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