Senior Software Engineer Agentic AI

Job Description

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//C# SQL Server Azure) delivering trustworthy cost-efficient low-latency experiences in real customer workflows.

What Youll Do!

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 MTech stack: TypeScript/Angular /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.

Skills & Requirements

What You Bring!

Core AI & Agentic Expertise

Proven experience building LLM-powered applications with Azure OpenAI embeddings vector stores RAG prompt engineering and evaluation pipelines.

Hands-on with agent frameworks such as Semantic Kernel LangGraph LangChain Agents AutoGen or CrewAI.

Ability to design deterministic evaluatable and safe agent behaviors including function schemas tool success metrics fallback strategies.

Practical use of Prompt Flow for authoring testing and deploying multi-step AI workflows in Azure AI Foundry.

MCP Memory & Agentic Communication

Experience building and consuming MCP services to standardize tool access across agents.

Implemented memory architectures (episodic semantic vector graph) and long-running conversational context.

Designed agent-to-agent communication patterns (messaging orchestration delegation arbitration).

Microsoft Data & App Platform

Integration with Microsoft Fabric SQL Server Supabase Databricks (OneLake/Lakehouse/Warehouse/Real-Time) for grounding data retrieval and telemetry.

Working knowledge of Dataverse entities actions and triggers; connecting agents to line-of-business records and Power Platform workflows.

Databricks for ELT Delta Lake pipelines feature engineering ML training/serving MLflow tracking and model lifecycle.

Azure IoT Hub/IoT Edge pipelines to incorporate device telemetry and edge-to-cloud intelligence into agentic workflows.

Azure services: App Service/Functions/AKS Key Vault Storage Event Hubs/Service Bus Monitor/Application Insights.

Python & Backend Engineering

Production-grade Python (FastAPI asyncio type hints) Postgres/SQL Redis queues OpenTelemetry CI/CD and containerization.

Strong API design testing (unit/integration/property-based) performance tuning and reliability engineering.

Front-End & MTech Enterprise Stack

Experience in TypeScript/Angular for operator consoles and human-in-the-loop oversight.

Ability to integrate /C# SQL Server NServiceBus and Azure DevOps in our enterprise environment.

AI-Native Dev Workflow & Culture

Daily use of GitHub Copilot Bolt Cursor Replit and vibe-coding to speed delivery and raise quality.

Mentor teams in prompting agent behavior design context management evaluation and AI-assisted engineering practices.

Seasoned aptitude for action tight feedback loops crisp written communication and ownership mindset.

Success Looks Like (Outcomes)

Quality & reliability: rising agent tool-use success rate; falling hallucination/retry rates; low incident volume; fast MTTR.

Performance & cost: P50/P95 latency and token-cost budgets met; measurable efficiency gains across services.

Adoption & impact: shipped features used by real users; clear business KPIs improved via automation/intelligence.

Engineering excellence: high test coverage stable CI/CD observable systems and healthy on-call posture.

Tooling & Stack Summary

AI & Agentic: Azure AI Foundry (Azure OpenAI Prompt Flow evaluations) MCP Semantic Kernel LangGraph LangChain AutoGen CrewAI HuggingFace embeddings vector DBs Azure AI/Cognitive Search RAG memory architectures.

Data & Integration: Databricks (ELT ML Delta Lake MLflow) Microsoft Fabric (OneLake/Lakehouse/Warehouse/Real-Time) Dataverse Event Hubs/Service Bus.

IoT: Azure IoT Hub IoT Edge stream ingestion & device telemetry flows.

Services: Python (FastAPI asyncio) .NET/C# REST/gRPC containers CI/CD with Azure DevOps.

Frontend: TypeScript/Angular Ionic; E2E testing with Cypress.

AI-Native Dev Tools: GitHub Copilot Bolt Cursor Replit vibe-coding workflows.

About the company

MTech Systems helps the food production industry increase yield improve animal welfare and achieve sustainability. Over 150 leading animal-protein producers rely on our secure cloud-based platform to keep comprehensive information across their operations and supply chain. No matter the size or complexity of the scenarios.

From independent farmers to multinational integrators from feed producers to food processors and every supply chain player in between get to easily digitalize their operations with MTech Systems.

With Amino our flagship product and foundational platform any producer can kickstart their digitalization journey.

Our approach agnostic to any hardware and other information systems enables entire production teams to easily extract data directly from the field. With a centralized database and intuitive dashboards thousands of MTech users make informed decisions and achieve their business goals every day.