Senior .NET Engineer (US Citizen/Hybrid/DataBricks/AI/PublicTrust Required)

Senior .NET Engineer (Databricks & AI) – Mission Feature Delivery IvoryCloud is seeking a Senior .NET Engineer to design and deliver enterprise applications for a high-visibility federal mission environment.

The role centers on production .NET application engineering, with significant work developing in and integrating Databricks products and AI capabilities into the application ecosystem. The right candidate is a senior software engineer first: someone who builds secure, maintainable, production-grade .NET applications and APIs and has expanded their engineering expertise into modern data platforms and AI-enabled application development. This person will bring hands-on Databricks and AI engineering experience to connect enterprise applications with mission data, generative AI capabilities, and automated workflows. This is a hands-on engineering role spanning application architecture, front-end and back-end development, data integration, and modern AI development. Candidates whose AI experience is limited primarily to using GitHub Copilot, Claude, ChatGPT, or other coding assistants for software development will not meet the AI engineering requirement for this role.

What You'll Do Design, develop, test, and deploy production enterprise applications and APIs using .NET, C#, and modern SPA frameworks, with Angular preferred. Apply object-oriented design, SOLID principles, and clean architecture to build maintainable, testable, and scalable solutions. Write efficient SQL and ORM-based data access, including technologies such as Entity Framework, and tune database performance. Integrate .NET applications with the Databricks Data Intelligence Platform, including Delta Lake, Databricks SQL, Unity Catalog, model serving, and Databricks Apps. Build and support Databricks data pipelines and workflows using Python/PySpark, Spark SQL, and medallion architecture. Develop generative AI features, agentic workflows, and AI agents embedded within enterprise applications that interact with enterprise data, APIs, tools, and business processes. Build RAG and knowledge-retrieval capabilities, including document ingestion, extraction, chunking, retrieval, grounding, and evaluation. Integrate LLMs and foundation models into enterprise applications through governed APIs and model-serving endpoints. Design integrations between application, data, and AI services using secure APIs and reusable engineering patterns. Implement secure authentication and authorization, secrets management, data-access controls, and secure coding practices across application, data, and AI services. Establish automated testing for traditional applications and AI-enabled features, including unit, integration, and regression testing as well as AI evaluation for correctness, retrieval quality, reliability, and safety. Diagnose and resolve performance, scalability, cost, data-quality, and reliability issues across application, data, and AI workloads. Contribute to CI/CD pipelines, automated deployment, source-control practices, and production release processes. Participate in architecture and technical design decisions and translate business and mission

requirements into technically feasible solutions. Work directly with product owners, developers, data engineers, analysts, and federal technical stakeholders. Mentor developers and help establish reusable engineering patterns and standards across .NET, Databricks, data, and AI development. Evaluate emerging technologies and determine where they provide meaningful value within the existing enterprise architecture rather than introducing technology for its own sake. Required

Qualifications 8+ years of professional software engineering experience, including significant hands-on development of production enterprise applications. Strong production application-development experience with .NET/C#, REST APIs, and modern SPA technologies. Strong understanding and practical application of object-oriented programming, SOLID principles, clean architecture, and software design patterns. Experience writing efficient SQL and working with ORM technologies such as Entity Framework. Experience with database design, query optimization, and performance tuning. 3+ years of hands-on experience with Databricks or comparable modern data platforms such as Microsoft Fabric or Snowflake, including delivery of production or production-scale workloads. Direct Databricks experience is strongly preferred. Hands-on experience with Python/PySpark and Spark SQL for modern data-platform and AI workloads. Strong experience with Apache Spark and distributed data processing concepts. Hands-on experience designing, implementing, or maintaining Delta Lake, Lakehouse, or comparable modern data architectures. Understanding of medallion architecture and modern data-engineering patterns. Hands-on experience building at least one of the following in a production or production-like environment: RAG application Agentic workflow or AI agent Tool-calling workflow Intelligent document-processing capability LLM-enabled enterprise application Experience with structured and unstructured document ingestion, extraction, transformation, and retrieval. Experience integrating AI-enabled applications with enterprise data sources, APIs, tools, and business processes. Experience in integrating LLMs or foundation models into applications using APIs, managed model services, or model-serving endpoints. Understanding of AI application evaluation, including approaches for evaluating retrieval quality, correctness, reliability, and failure conditions. Strong understanding of REST APIs, authentication and authorization, secrets management, secure coding, Git, CI/CD, and production deployment practices. Ability to independently take a use case through the full engineering lifecycle: technical discovery → architecture → prototype → implementation → testing/evaluation → production deployment. Ability to communicate technical tradeoffs, risks, and recommendation