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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer, Back-End .NET - **Company:** Frontline Education - **Location:** Florence, KY, United States (Remote available) - **Experience:** Expert - **Salary:** $160,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** ASP.NET, .NET Framework, Multitier Architecture, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Audit Trail, Automation of Tests, Microsoft Azure, Big Data, C Sharp (Programming Language), Law Practice Management Software, Cloud Engineering, Software Quality, Continuous Integration, Command-Query Responsibility Segregation (Software Development), Data Integrity, Data Mining, Data Security, Relational Databases, Decision Support Systems, Dependency Injection, DevOps, Document Management Systems, Distributed Systems, Github, Information Retrieval, Key Management, Machine Learning, Microsoft Software, Microsoft SQL Server, Performance Tuning, RabbitMQ, OpenAI, Search Technologies, Software Engineering, Data Streaming, Systems Integration, Software Vulnerability Management, Microsoft Agent Framework, Data Logging, Google Cloud, Enterprise Software Applications, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Model Validation, Caching, Technical Debt, Indexer, Backend, Event Driven Architecture, AI Platforms, Infrastructure Automation Frameworks, Maintaining Code, Enterprise Integration, Apache Kafka, Build Tools, Operational Systems, Machine Learning Operations, Asynchronous Programming, Event Sourcing, Api Design, Api Gateway, Restful APIs, Terraform, Prompt Orchestration, Domain Driven Design, Intelligent Document Processing, Software Version Control, Sql Tuning, Dynatrace, Automation Anywhere, Docker, Microservices - **Published:** October 7, 2026 - **Apply:** https://www.nettemps.com/us/en/W5353A5DD7B2FBB7C3F.ntap ## About the Role 10+ years of professional software engineering experience, with significant experience designing and building enterprise Back End systems. Deep expertise with C#, .NET, ASP.NET Core, RESTful APIs, background services, dependency injection, asynchronous programming, and modern Back End engineering practices. Strong experience with enterprise application architecture, including microservices, modular monoliths, distributed systems, event-driven patterns, messaging, API gateways, and service-to-service communication. Experience designing and operating production systems in cloud environments such as AWS, Azure, or Google Cloud, with a preference for AWS-based enterprise platforms. Hands-on experience integrating AI, machine learning, or LLM-enabled capabilities into business workflows, enterprise applications, or operational systems. Experience with data-intensive applications, including relational databases, SQL performance tuning, data modeling, caching, indexing, and integration with analytics or search platforms. Strong understanding of secure software development practices, including authentication, authorization, encryption, secrets management, secure APIs, and vulnerability management. Experience working in or supporting regulated, compliance-driven, or risk-sensitive industries such as financial services, healthcare, insurance, legal technology, government, life sciences, audit, risk, or compliance software. Demonstrated ability to lead complex technical initiatives across teams, influence architecture, and deliver high-impact engineering outcomes. Excellent communication skills with the ability to explain technical decisions, risks, and tradeoffs to engineering, product, security, compliance, and executive stakeholders. Preferred Qualifications Experience with AWS Bedrock, OpenAI APIs, Microsoft Agent Framework, SpecKit, vector databases, embeddings, retrieval-augmented generation, prompt orchestration, and AI workflow automation platforms. Experience designing human-in-the-loop workflows, approval flows, audit trails, or exception management systems for AI-assisted business processes. Familiarity with responsible AI practices, model evaluation, AI governance, prompt/version control, AI observability, and risk management frameworks. Experience with enterprise workflow platforms, rules engines, BPM tools, case management systems, document management systems, or compliance operations platforms. Experience with messaging and event streaming technologies such as Kafka, RabbitMQ, or Event Grid. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Experience with DevOps and infrastructure-as-code practices using tools such as GitHub Actions and Terraform. Experience with domain-driven design, clean architecture, CQRS, event sourcing, distributed tracing, and high-scale API platforms. Ideal Candidate Profile The ideal candidate is a hands-on principal-level engineer who can move comfortably between code, architecture, strategy, and cross-functional leadership. You have built complex enterprise systems, understand the realities of regulated environments, and know how to introduce emerging technologies without creating unnecessary risk. You are pragmatic about AI. You understand its potential, but you also recognize the importance of accuracy, governance, auditability, security, cost management, and human oversight. You can help teams separate hype from durable product value and turn ambiguous opportunities into well-designed, production-ready capabilities. You are equally comfortable mentoring engineers, reviewing architecture, writing critical code, facilitating technical discussions, and partnering with senior leaders to shape product and platform direction. Leadership Expectations As a Principal Engineer, you will be expected to lead by influence, not just by implementation. You will help teams make better technical decisions, improve engineering discipline, and develop systems that can scale with the business. You should bring strong judgment, intellectual humility, technical depth, and a bias toward practical delivery. We value engineers who can simplify complexity, communicate clearly, and build trust across functions. Position Requirements Summary * Deep Back End engineering expertise in C# and .NET * Enterprise architecture experience across complex distributed systems * Practical experience integrating AI workflows into production applications * Strong judgment in regulated, compliance-sensitive environments * A security-first and audit-ready engineering mindset * Proven ability to influence across teams and mentor senior engineers * A track record of delivering high-quality, scalable enterprise software ## Description We are seeking a Principal .NET Software Engineer to help lead the evolution of our enterprise platform in a highly regulated, compliance-driven industry. This role is ideal for a senior technical leader who has deep expertise in building scalable Back End systems with the Microsoft technology stack and AWS, with hands-on experience integrating AI-enabled workflows into real-world enterprise workstreams. As a Principal Engineer, you will operate at the intersection of architecture, product delivery, engineering excellence, and applied AI. You will be expected to design and deliver resilient Back End services, guide technical strategy, mentor senior engineers, and help establish practical patterns for safely incorporating AI capabilities into production systems where accuracy, auditability, security, and compliance are critical. This is not a purely research-focused AI role. We are looking for someone who understands how to apply AI pragmatically inside enterprise software: automating workflows, enhancing decision support, improving data extraction, enabling intelligent recommendations, streamlining compliance operations, and embedding human-in-the-loop controls where needed. Key Responsibilities Technical Leadership & Architecture Lead the design, development, and modernization of enterprise-grade Back End systems using C#, .NET, ASP.NET Core, Microsoft SQL Server, APIs, microservices, event-driven architecture, and cloud-native patterns. Define and influence architectural direction for critical capabilities, ensuring solutions are scalable, secure, observable, maintainable, and aligned with long-term product strategy. Serve as a technical authority across engineering teams, helping evaluate tradeoffs related to performance, resiliency, data integrity, compliance, integration complexity, and operational supportability. Partner with engineering leadership, product management, architecture, security, compliance, platform teams and data teams to translate complex business and regulatory requirements into durable technical solutions. Establish reusable engineering patterns, reference architectures, and implementation standards for Back End services, API design, data access, integrations, and AI-enabled workflow components. AI Workflow Integration Design and implement Back End services that integrate AI capabilities into enterprise workstreams, including use cases such as intelligent document processing, classification, summarization, anomaly detection, recommendation workflows, knowledge retrieval, workflow automation, and decision support. Work with product, compliance, legal, and security stakeholders to ensure AI-enabled features are implemented with appropriate controls, explainability, audit trails, data protection, and human review mechanisms. Collaborate with data science, platform, and vendor teams to integrate LLMs, AI services, model APIs, vector search, retrieval-augmented generation patterns, prompt orchestration, and workflow automation tools into production software. Help define engineering standards for responsible AI usage, including model interaction logging, prompt/version management, evaluation strategies, fallback handling, access controls, and monitoring for quality, latency, cost, and risk. Identify opportunities to use AI to improve internal engineering and operational workstreams, including developer productivity, testing, support triage, compliance reviews, and operational analysis. Regulatory, Security & Compliance Alignment Build systems that meet the expectations of regulated environments, including strong controls around data privacy, auditability, traceability, identity, authorization, retention, and change management. Ensure software designs account for compliance obligations, risk management practices, secure SDLC standards, and enterprise governance requirements. Partner with security and compliance teams to support threat modeling, secure architecture reviews, audit readiness, incident response planning, and evidence generation. Design AI-enabled workflows with appropriate safeguards, including data minimization, role-based access, explainable outputs, human approval gates, and defensible records of system behavior. Engineering Excellence Set a high bar for code quality, automated testing, reliability, observability, CI/CD practices, and production readiness. Drive improvements in system performance, scalability, reliability, and maintainability across core Back End services. Review complex designs and code changes, providing constructive technical guidance to engineers at all levels. Lead efforts to reduce technical debt, modernize Legacy components, improve integration patterns, and simplify system complexity. Promote strong operational practices, including structured logging, distributed tracing, metrics, alerting, runbooks, and post-incident learning. Mentorship & Cross-Functional Influence Mentor senior and staff-level engineers, helping them grow in architecture, technical decision-making, system design, and leadership. Influence engineering direction across multiple teams without relying solely on formal authority. Communicate clearly with technical and non-technical stakeholders, especially when explaining complex architecture, compliance implications, AI limitations, and delivery tradeoffs. Act as a trusted advisor to product and engineering leadership on how to safely and effectively incorporate AI capabilities into enterprise product experiences.