Senior Dynamics 365 Software Developer

Role Description

The primary responsibility of the Senior Software Engineer is to lead and contribute to the design, development, testing, and maintenance of FIELDBOSS software solutions across Dynamics 365 Customer Engagement, Business Central, and the Power Platform. This role requires a combination of technical expertise and collaboration with other team members. The Senior Software Engineer will ensure that the software development process is efficient and aligned with organizational goals and best practices. This role contributes to the development and support of FIELDBOSS AI agents, and applies AI development tools to improve coding efficiency, test code coverage, and test automation. Mentoring, coaching, and leadership are essential qualities for this role.

Objectives

· Maximize the quality and efficiency of existing code and Engineering processes.

· Assist with improving development best practices.

· Design new code, features, and processes to ensure scalability of FIELDBOSS.

· Maintain existing versions of FIELDBOSS code base and supporting utilities.

· Collaborate with other departments to ensure all technical areas of FIELDBOSS align with project requirements and company goals.

· Provide leadership and guidance to junior engineers, including on AI agent development practices.

· Design, build, and maintain FIELDBOSS AI agents that are accurate, explainable, and reviewed by a person before action is taken.

· Advance AI development and AgentOps practices across the Engineering team, ensuring AI features meet safety, governance, and auditability standards.

Responsibilities

· Develop new application features for FIELDBOSS using C#, JavaScript, T-SQL, AL, and Power FX.

· Create Dynamics 365 plugins, custom workflow activities, Custom APIs, JavaScript web resources and Client API scripts, Canvas Apps, and Power Automate flows.

· Configure and extend model-driven apps, including forms, views, business rules, and Dataverse security and data model changes.

· Build and maintain integrations between FIELDBOSS, Business Central, and third-party systems.

· Manage solutions, deployments, and release pipelines across development, test, and production environments.

· Maintain and enhance existing FIELDBOSS code and customizations.

· Customize and create Business Central codeunits, pages, tables, queries, and reports.

· Design and develop unique software features for individual FIELDBOSS customers.

· Develop reusable engineering utilities and assets.

· Create and install FIELDBOSS upgrades, patches, and hotfixes.

· Resolve issues and technical challenges that arise in previous versions of FIELDBOSS.

· Design and develop FIELDBOSS AI agents using Azure AI Foundry, Copilot Studio, and Power Platform, integrated with the Dataverse and FIELDBOSS data model.

· Build agent orchestration and integration layers using Power Automate, Azure Logic Apps, Azure Service Bus, Azure Functions, and Microsoft Teams, including the JSON schemas and secure APIs they rely on.

· Apply prompt and context engineering, and evaluate agent accuracy and reliability through testing, regression checks, and telemetry.

· Implement AI guardrails, security, auditability, and governance, and support deployed agents through prompt and model versioning, monitoring, and rollbacks.

· Use GitHub Copilot and other AI-assisted development tools to improve engineering throughput, code quality, test code coverage, and test automation.

· Guide and mentor junior engineers and ensure that the team follows best practices and coding standards.

· Conduct and participate in code reviews to maintain code quality and ensure that best practices are followed.

· Create and maintain documentation for the software architecture, codebase, and development processes.

· Collaborate with testers to ensure FIELDBOSS meets quality standards.

· Assist with the automation of manual engineering processes.

Measurement

· Completion of assigned tasks on time.

· Quality of FIELDBOSS code measured by product stability.

· Ability to independently resolve bugs and roll out fixes.

· Collaboration with team members and other departments.

· Ability to adapt to changing project requirements and new technologies.

· Alignment with company goals to deliver a quality product, improve revenue growth, and deliver operational efficiencies.

· Improve efficiencies when deploying FIELDBOSS patches, hotfixes, and upgrades.

· Ability to provide effective mentorship to improve the performance of junior engineers, including on AI agent development.

· Quality, reliability, and adoption of FIELDBOSS AI agents, and successful delivery of new agents against the AI roadmap.

· Adherence to AI safety, governance, and auditability standards, supported by telemetry and regression testing that catches agent issues before they reach customers.

· Efficiency gains from AI-assisted development tools, including increased test code coverage and test automation.

Skills and Experience

Software Engineering

· C#

· .NET

· T-SQL and SQL Server

· REST APIs and secure API development

· Event-driven architecture

· Microservices and asynchronous processing

· JSON schema design

· Automated unit and integration testing

· Debugging and performance troubleshooting

· Source control and CI/CD

· GitHub Copilot assisted development

Dynamics 365 and Power Platform

· Dynamics 365 Customer Engagement SDK

· Plugins and custom workflow activities

· Custom APIs and custom actions

· JavaScript web resources and Client API

· Model-driven apps, forms, views, and business rules

· Microsoft Dataverse data modeling and security

· FetchXML and the Dataverse Web API

· Canvas Apps and Power FX

· Power Automate

· Business Central AL development

· Solution management, ALM, and deployment

· Azure integration services, including Functions, Logic Apps, and Service Bus

· Microsoft Teams integration

AI and Agent Development

· Agentic application design

· Azure AI Foundry and Copilot Studio

· Prompt and context engineering

· Retrieval-Augmented Generation (RAG)

· LLM evaluation and testing

· AI safety, guardrails, and governance

AI Operations (AgentOps)

· Prompt and model version management

· AI telemetry and monitoring

· Regression testing and evaluation frameworks

· Production AI deployments, incident response, and rollbacks

Data and Analytics

· Relational and Dataverse data modeling

· Structured and unstructured data processing

· Data governance

· Reporting and analytics

· Microsoft Fabric

Additional Requirements

· Willingness to work outside of regular business hours when required.