AI Software Engineer Intern

Overview We are seeking an innovative AI Software Engineer to design, build, and deploy advanced software solutions that transform both internal mortgage operations and external customer experiences. This role combines software engineering, artificial intelligence, cloud-native infrastructure, and mortgage-industry problem-solving to deliver tools that increase efficiency, enhance customer engagement, and support data-driven decision-making across the organization. AI-Driven Software Development Architect, develop, and deploy AI-powered applications for internal operations (e.g., Build customer-facing and marketing-facing software such as intelligent chat assistants, personalized loan recommendation engines, automated prequalification tools, and interactive calculators. Integrate AI models (LLMs, predictive models, generative AI) into new or existing products using modern development frameworks and APIs. Cloud Infrastructure & Deployment Design, deploy, and operate applications on Microsoft Azure, using services such as Azure Kubernetes Service (AKS), App Service, Azure Functions, Azure SQL, Storage, Key Vault, and Azure OpenAI / AI Foundry. Containerize applications with Docker and run them on Kubernetes. This includes writing and maintaining manifests and Helm charts, and managing deployments, scaling, ingress, secrets, and resource limits. Build and maintain CI/CD pipelines (Azure DevOps or GitHub Actions) that take code from commit to production reliably and repeatably. Manage cloud resources with infrastructure-as-code (Terraform, Bicep, or ARM templates). Implement monitoring, logging, and alerting (Azure Monitor, Application Insights, Log Analytics) to keep production AI services healthy, and troubleshoot cluster and application issues when they come up. Apply cloud security best practices, including Entra ID (Azure AD) identity and role-based access, managed identities, network isolation, and secure secrets handling. All of this should meet the data-protection requirements for sensitive borrower information. Optimize cloud cost and performance for AI workloads, including model hosting, inference scaling, and GPU/compute usage. Partner with operations, loan officers, compliance, marketing, and customer experience teams to identify high-impact use cases for AI and translate them into scalable products. Work closely with data engineering to source, prepare, and validate datasets used for model training and evaluation. Develop secure, compliant, and well-documented systems aligned with mortgage regulatory requirements. Train, fine-tune, or customize AI models to improve accuracy, performance, and relevance to mortgage workflows. Implement continuous monitoring, versioning, and quality checks for AI models in production. Evaluate emerging AI technologies and recommend adoption paths for the organization. Establish development standards for AI-enabled software, including testing strategies, documentation, and model governance. Provide guidance on responsible AI usage, data protection, and fair lending considerations in all deployments. Contribute to long-term AI strategy to modernize the company’s tech stack and customer experience. Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience). ~3–5+ years of software engineering experience building web or backend applications. ~ Hands-on experience with machine learning or generative AI tools (OpenAI, Anthropic, HuggingFace, LangChain, vector databases, etc.). ~ Proficiency in languages such as Python, TypeScript/JavaScript, or C#. ~ Strong working knowledge of Microsoft Azure, including hands-on experience deploying, securing, and operating production workloads (compute, networking, identity, storage, and Key Vault). ~ Solid experience with containers and Kubernetes (preferably AKS), including deployments, services, ingress, config/secrets, autoscaling, and debugging workloads with kubectl. ~ Experience building and maintaining CI/CD pipelines for containerized applications. ~ Understanding of APIs, microservices, and modern software architecture patterns. Experience in fintech or mortgage/lending systems. Familiarity with mortgage workflows: Microsoft Azure certifications (e.g., AZ-204 Developer, AZ-104 Administrator, AZ-305 Solutions Architect, or AI-102 AI Engineer) and/or Kubernetes certifications (CKA or CKAD). Experience with infrastructure-as-code (Terraform or Bicep) and GitOps or Helm-based deployment workflows. Experience deploying and scaling AI/LLM workloads on Azure (Azure OpenAI, AI Foundry, or self-hosted models on AKS). Knowledge of MLOps tools and frameworks for model deployment. Experience building customer-facing digital experiences. Ownership of systems in production, from architecture through deployment, monitoring, and incident response. Curiosity and eagerness to explore new AI capabilities. Commitment to data security, fair lending, and responsible AI use. Enhanced digital customer experience through AI-driven tools and automation. Scalable marketing technology that personalizes outreach and increases conversion. Secure, reliable, cloud-native infrastructure that lets AI products scale with the business. A forward-thinking, innovative culture that positions the company as a technology leader in the mortgage industry.