AI Automation Software Engineer

Our client is seeking a highly capable AI & Automation Software Engineer. You will not just be writing basic scripts; you will be architecting the data pipelines and AI agents that power our managed services. We need a builder who can securely bridge Large Language Models with our enterprise infrastructure using modern frameworks like the Model Context Protocol (MCP) and Databricks/SQL Database ETL pipelines. Note to Applicants: A verifiable portfolio of your work (GitHub, architecture teardowns, or live projects) is an absolute requirement for this role. We are looking for proven execution. Core Responsibilities Agentic Workflows & MCP: Design and deploy custom Model Context Protocol (MCP) servers (using Python or .NET) to allow AI agents (like Copilot Studio) to securely interact with our infrastructure and APIs. ETL & Data Engineering: Build and maintain scalable data pipelines using PySpark, Databricks, and SQL Databases. Implement Medallion Architecture (Bronze, Silver, Gold layers) for robust data ingestion from third-party REST APIs. AI & Vector Databases: Architect RAG (Retrieval-Augmented Generation) pipelines. Deploy, populate, and maintain vector databases to feed contextual data to LLMs. Model Training & Fine-Tuning: Curate large, complex datasets to fine-tune machine learning models and LLMs for highly specific IT and managed service use-cases. Cloud Orchestration: Develop within the Azure ecosystem, utilizing Azure Container Apps, Azure Automation (Runbooks), Entra ID (Service Principals/Managed Identities), and Data API Builder. Advanced Automation: Work with automation platforms (Azure Logic Apps / Power Automate) to connect disparate systems (Microsoft Graph API, RMM tools, billing platforms) into seamless, zero-touch workflows. Required Qualifications Experience: 3+ years of hands-on software development and data engineering experience (this is not an entry-level or fresh-graduate role). Programming: Deep proficiency in Python and/or C# (.NET) . You must know how to write clean, scalable, and highly secure code. API Mastery: Extensive experience building, consuming, and authenticating RESTful APIs, specifically dealing with pagination, rate limiting, and complex JSON payloads. Database Infrastructure: Strong SQL skills (T-SQL / Azure SQL). Experience with modern cloud data warehouses (Snowflake, Databricks) is highly preferred. Security-First Mindset: Understanding of cloud security paradigms—you know why an LLM should never have direct, un-containerized access to a raw database. Portfolio Requirement You must submit a portfolio of past work. Examples of what we want to see: Code repositories demonstrating complex API integrations or ETL pipelines. Custom AI agents, RAG implementations, or MCP servers you have built. Architecture diagrams or white-papers you've authored detailing a problem you solved using Azure, Data, or AI.