We are seeking an experienced and innovative Senior AI Software Engineer to develop and deploy our next-generation, production-grade AI systems. In this role, you will be responsible for orchestrating robust Python-based back-end architecture, integrating state-of-the-art Large Language Models (LLMs), optimizing high-performance vector databases, and deploying scalable, secure APIs natively on Microsoft Azure. You will work closely with our Original Equipment Manufacturers (OEM) customers to agree on new requirements, develop plans to deliver solutions using Agile processes, and ensure strict adherence to software quality standards throughout the development lifecycle.Focus Areas & Core Responsibilities:AI Systems DevelopmentArchitect, write, and maintain clean, production-grade, and testable AI-driven software and back-end services using Python. Implement comprehensive testing, validation, and evaluation strategies to ensure the safety and reliability of model outputs.API & Cloud DeploymentBuild, secure, and deploy high-performance APIs and micro-services on Microsoft Azure using server-less workflows (e.g., Azure Functions).Vector Search & RetrievalIntegrate, structure, and optimize vector databases (e.g., PGVector, Qdrant, Milvus, or Azure AI Search) to power Retrieval-Augmented Generation (RAG) pipelines and high-speed semantic search.LLM IntegrationProgrammatically interface with commercial and open-source LLMs through Python-based APIs, establishing reliable workflows for caching, rate-limit handling, and token usage optimization.Big Data & PipelinesDesign and implement scalable data processing pipelines on platforms like Azure Databricks or Microsoft Fabric. Manage data progression through a Medallion Architecture to power AI systems.MLOps & DeploymentOwn the end-to-end ML lifecycle on Azure. Architect and maintain CI/CD pipelines in Azure DevOps, using Docker and Azure Kubernetes Service (AKS) to create scalable and reproducible ML workflows.Customer & Requirement ManagementPartner directly with OEM customers to elicit, clarify, and agree upon technical requirements. Translate customer business needs into structured technical plans and deliver high-quality solutions to those specifications.Agile Delivery & WorkflowsActive participation in Agile/Scrum methodologies. Use version control (Git) daily and manage development workflows, tasks, and documentation using tools like Jira or Microsoft Azure DevOps (ADO).Quality Process AdherenceAdhere strictly to internal software quality processes and industry best practices, including rigorous peer code reviews, automated testing, continuous integration, and compliance standards.
