Senior GenAI and Azure Developer

Forvis Mazars is a global leader in audit & assurance, tax, advisory and consulting services. Operating in over 100 countries and territories, our 40,000+ strong team is committed to delivering an unmatched client experience, bringing clarity and helping our clients confidently prepare for what’s next. Why join us Our people are ambassadors and leaders and have a bold entrepreneurial spirit to shape the future of our industry and the communities within which we serve. We empower and develop our teams to become professionals of the highest calibre in technical and client excellence. Our people first approach offers our teams a caring work environment which promotes belonging and inclusivity of all cultures and perspectives. The Position We are looking for a Senior GenAI and Azure Developer to join our team and work remotely with Ireland-based teams. The Senior GenAI and Azure Developer will support the design, development and deployment of generative AI and automation solutions within the firm. The role will have a strong focus on building secure, scalable and production-ready AI applications using Microsoft Azure and Microsoft Foundry. The successful candidate will bring practical experience in building generative AI solutions, together with an in-depth understanding of Azure and how its services, security model and networking behave, so that they can design, build and troubleshoot applications effectively. The candidate will help the team move solutions from business requirements to initial proof of concept through to secure deployment and ongoing production support. The position requires a strong technical foundation, together with the ability to apply appropriate architecture, security, governance and quality standards throughout the solution lifecycle.

Key Responsibilities
Generative AI Development & Research Design & Development
• Design and develop generative AI applications aligned with defined business requirements, using Microsoft Foundry and related Azure AI services.
• Select and implement the right solution pattern for each use case, from direct LLM-based pipelines to grounded solutions that draw on enterprise knowledge and agentic approaches for complex, multi-step or tool-enabled workflows.
• Build the data and retrieval layers that ground AI solutions in enterprise content, including ingestion, ontologies, indexing, graph, search, permission-aware access and clear citations.
• Develop AI assistants and agent-based solutions using pro-code and low-code approaches across Microsoft Foundry, Copilot Studio and related technologies, integrating with enterprise data sources, APIs, Microsoft 365 and approved business systems.
• Contribute to reusable technical patterns and components, following established engineering and governance standards. Testing & Optimisation
• Develop and carry out testing to ensure AI solutions meet quality, performance, security and compliance requirements, using representative business scenarios, edge cases and known failure conditions.
• Evaluate the accuracy, relevance and groundedness of responses, and apply prompt refinement, retrieval tuning and model-level adjustments to improve quality and reduce hallucinations.
• Perform regression testing when models, prompts, data sources or application components change.
• Use monitoring, tracing and evaluation tools to identify improvements, balancing performance, latency, reliability and cost. Innovation & Research
• Stay informed of developments in generative AI, agentic AI, Microsoft Foundry and Azure, and assess new models, frameworks and platform capabilities against practical business and technical requirements.
• Participate in proofs of concept and pilot initiatives to assess feasibility, risk and value, ensuring each has a realistic route to secure production deployment.
• Evaluate when managed Microsoft capabilities are appropriate and when a more configurable or custom implementation is required.
• Present technical findings and recommendations clearly to technical and non-technical stakeholders. Azure Solution Development
• Design and build GenAI and automation applications on Azure, selecting the appropriate services for each requirement, such as Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Functions, App Service, Container Apps, Storage, Cosmos DB, AI Gateway, MCP server, Key Vault and API Management.
• Apply a solid understanding of Azure architecture to design decisions on availability, resilience, scalability, performance and cost.
• Implement secure access using Microsoft Entra ID, managed identities, Azure role-based access control and Key Vault.
• Develop applications that work correctly in secured, privately networked environments, understanding the effect of private endpoints, private DNS and disabled public access, and diagnosing connectivity issues from the application side.
• Work within the organisation’s Azure landing zones, policies and environment structure (development, testing, staging and production).
• Build, test and deploy applications using Git, Azure DevOps pipelines and containers, working with established pipelines and templates provided by platform teams.
• Prepare clear infrastructure, networking and access requirements when support from IT or Cloud Platform teams is needed. Security by Design & Responsible AI
• Apply security-by-design and privacy-by-design principles throughout the solution lifecycle, ensuring that users, applications and AI agents only access the data, documents and tools they are authorised to use.
• Implement safeguards against prompt injection, jailbreak attempts, harmful content and unauthorised information retrieval, treating retrieved and external content as potentially untrusted.
• Ensure that personal, confidential or sensitive information is appropriately protected in prompts, outputs and operational logs.
• Include human review and approval where an AI-supported action is sensitive, external-facing or difficult to reverse.
• Follow the firm’s Responsible AI, data-protection, information-security and governance requirements. Process Improvement
• Support the identification and assessment of business processes for automation opportunities.
• Implement practical, maintainable solutions that improve efficiency, reduce errors and align with the intended business outcome. Monitoring & Maintenance
• Monitor deployed AI and automation solutions for reliability, performance and cost using Azure Monitor, Application Insights, Log Analytics and relevant Microsoft Foundry capabilities.
• Configure appropriate logging and alerts while avoiding unnecessary storage of personal or confidential information.
• Investigate and resolve issues across the application, data, integration and Azure service layers, escalating infrastructure and network matters to platform teams where appropriate.
• Support controlled production releases, rollback and recovery, and apply fixes and enhancements as incidents, process changes or requirements evolve. Integration & Collaboration
• Work with business stakeholders to translate requirements into suitable AI, Azure and automation solutions, supporting requirements gathering, user acceptance testing and iterative improvement.
• Collaborate with developers, IT, Cloud Platform, security, risk, compliance and data-protection teams, and integrate solutions with Microsoft 365, enterprise databases, APIs and approved external services.
• Explain technical options, dependencies, risks and costs clearly, and review proofs of concept to identify what is required to make them secure, maintainable and production-ready.
• Support other team members through technical guidance, code reviews and knowledge sharing. Governance & Best Practices
• Follow established ethical guidelines, data-protection requirements and internal governance policies.
• Maintain appropriate source-control, versioning (including prompts and configurations), testing and release standards.
• Document key technical decisions, risks and limitations, and contribute to reusable engineering standards and approved solution patterns. Documentation & Knowledge Sharing
• Maintain technical documentation for AI and automation solutions, including architecture diagrams, data flows, deployment instructions and operational runbooks.
• Document the Azure resources, identities, permissions and integrations a solution depends on, along with its data ingestion, retrieval and evaluation approach.
• Support the development of user guides and training materials, and share lessons learned through code reviews and technical walkthroughs. Principal Requirements Education
• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Cloud Computing or a related technical field.
• Advanced degrees or relevant Microsoft Azure certifications are an advantage. Experience
• At least 5 years’ experience in software development, AI engineering or a related technical role.
• Practical experience designing and delivering generative AI solutions, from business requirements to proof of concept through to production.
• Strong experience developing, deploying and supporting applications within Microsoft Azure, including secure or privately networked environments.
• Experience working with CI/CD pipelines, source control and controlled release processes.
• Experience working with enterprise IT, Cloud Platform or security teams, and taking technical ownership of application and deployment issues. Skills & Competencies Technical Expertise: AI
• Strong understanding of generative AI solution architectures and implementation patterns, including LLM applications, knowledge-grounded solutions, agentic AI, orchestration frameworks and AI-enabled automation.
• Hands-on experience designing, developing and deploying AI applications using Microsoft Foundry, Azure OpenAI, Azure AI Services and related technologies.
• Experience integrating AI solutions with enterprise knowledge sources, business systems, APIs and tools, including retrieval, search, grounding, reasoning, workflow orchestration and action execution capabilities where appropriate.
• Experience evaluating, testing and optimising AI solutions, including response quality, grounding, agent behaviour, reliability, performance, security and cost.
• Strong understanding of the security, governance, privacy and operational risks associated with generative and agentic AI, together with appropriate mitigation and control approaches. Technical Expertise: Azure
• Strong hands-on experience developing and deploying applications in Microsoft Azure, using services such as Azure Functions, App Service or Container Apps.
• Experience with Azure Storage, Key Vault, API Management, Cosmos DB and application-monitoring services.
• In-depth working knowledge of Azure networking as it affects application development (virtual networks, private endpoints, private DNS and restricted public access), sufficient to build and troubleshoot applications in private environments without needing to administer the network.
• Understanding of Microsoft Entra ID, managed identities and Azure role-based access control.
• Working knowledge of Git, Azure DevOps CI/CD pipelines and Docker; experience with Bicep, Terraform or another infrastructure-as-code technology is beneficial. Programming Skills
• Strong proficiency in Python.
• Experience developing backend services, integrating REST APIs and working with databases, search services and Azure resources.
• Understanding of secure application configuration, error handling, logging and dependency management.
• Experience with PowerShell, JavaScript, TypeScript or C# is beneficial. Technical Expertise: Automation
• Experience developing workflows using Microsoft Power Automate and the Power Platform, integrated with Microsoft 365, Azure services and external APIs.
• Familiarity with Power Apps and approval-based workflows is beneficial. Additional Competencies
• Strong technical problem-solving and troubleshooting skills.
• Ability to take ownership of complex solutions and work independently.
• Strong collaboration and communication skills, including the ability to explain technical architecture, risks and dependencies clearly.
• Practical understanding of security, governance and production-readiness requirements. Personal Attributes
• Technically strong: Brings practical experience and can take ownership of complex technical challenges.
• Delivery focused: Understands what is required to move a solution from proof of concept into secure and reliable production use.
• Security conscious: Considers access, data protection and operational risk from the beginning.
• Pragmatic: Selects technology based on the business requirement, risk, maintainability and cost.
• Collaborative communicator: Works effectively with business stakeholders, developers, IT, Cloud Platform and security teams, and explains technical decisions and risks clearly.
• Adaptable and curious: Keeps up with changes in AI and Azure while assessing new technologies carefully before adoption. Generative AI Development & Research Design & Development
• Design and develop generative AI applications aligned with defined business requirements, using Microsoft Foundry and related Azure AI services.
• Select and implement the right solution pattern for each use case, from direct LLM-based pipelines to grounded solutions that draw on enterprise knowledge and agentic approaches for complex, multi-step or tool-enabled workflows.
• Build the data and retrieval layers that ground AI solutions in enterprise content, including ingestion, ontologies, indexing, graph, search, permission-aware access and clear citations.
• Develop AI assistants and agent-based solutions using pro-code and low-code approaches across Microsoft Foundry, Copilot Studio and related technologies, integrating with enterprise data sources, APIs, Microsoft 365 and approved business systems.
• Contribute to reusable technical patterns and components, following established engineering and governance standards. Testing & Optimisation
• Develop and carry out testing to ensure AI solutions meet quality, performance, security and compliance requirements, using representative business scenarios, edge cases and known failure conditions.
• Evaluate the accuracy, relevance and groundedness of responses, and apply prompt refinement, retrieval tuning and model-level adjustments to improve quality and reduce hallucinations.
• Perform regression testing when models, prompts, data sources or application components change.
• Use monitoring, tracing and evaluation tools to identify improvements, balancing performance, latency, reliability and cost. Innovation & Research
• Stay informed of developments in generative AI, agentic AI, Microsoft Foundry and Azure, and assess new models, frameworks and platform capabilities against practical business and technical requirements.
• Participate in proofs of concept and pilot initiatives to assess feasibility, risk and value, ensuring each has a realistic route to secure production deployment.
• Evaluate when managed Microsoft capabilities are appropriate and when a more configurable or custom implementation is required.
• Present technical findings and recommendations clearly to technical and non-technical stakeholders. Azure Solution Development
• Design and build GenAI and automation applications on Azure, selecting the appropriate services for each requirement, such as Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Functions, App Service, Container Apps, Storage, Cosmos DB, AI Gateway, MCP server, Key Vault and API Management.
• Apply a solid understanding of Azure architecture to design decisions on availability, resilience, scalability, performance and cost.
• Implement secure access using Microsoft Entra ID, managed identities, Azure role-based access control and Key Vault.
• Develop applications that work correctly in secured, privately networked environments, understanding the effect of private endpoints, private DNS and disabled public access, and diagnosing connectivity issues from the application side.
• Work within the organisation’s Azure landing zones, policies and environment structure (development, testing, staging and production).
• Build, test and deploy applications using Git, Azure DevOps pipelines and containers, working with established pipelines and templates provided by platform teams.
• Prepare clear infrastructure, networking and access requirements when support from IT or Cloud Platform teams is needed. Security by Design & Responsible AI
• Apply security-by-design and privacy-by-design principles throughout the solution lifecycle, ensuring that users, applications and AI agents only access the data, documents and tools they are authorised to use.
• Implement safeguards against prompt injection, jailbreak attempts, harmful content and unauthorised information retrieval, treating retrieved and external content as potentially untrusted.
• Ensure that personal, confidential or sensitive information is appropriately protected in prompts, outputs and operational logs.
• Include human review and approval where an AI-supported action is sensitive, external-facing or difficult to reverse.
• Follow the firm’s Responsible AI, data-protection, information-security and governance requirements. Process Improvement
• Support the identification and assessment of business processes for automation opportunities.
• Implement practical, maintainable solutions that improve efficiency, reduce errors and align with the intended business outcome. Monitoring & Maintenance
• Monitor deployed AI and automation solutions for reliability, performance and cost using Azure Monitor, Application Insights, Log Analytics and relevant Microsoft Foundry capabilities.
• Configure appropriate logging and alerts while avoiding unnecessary storage of personal or confidential information.
• Investigate and resolve issues across the application, data, integration and Azure service layers, escalating infrastructure and network matters to platform teams where appropriate.
• Support controlled production releases, rollback and recovery, and apply fixes and enhancements as incidents, process changes or requirements evolve. Integration & Collaboration
• Work with business stakeholders to translate requirements into suitable AI, Azure and automation solutions, supporting requirements gathering, user acceptance testing and iterative improvement.
• Collaborate with developers, IT, Cloud Platform, security, risk, compliance and data-protection teams, and integrate solutions with Microsoft 365, enterprise databases, APIs and approved external services.
• Explain technical options, dependencies, risks and costs clearly, and review proofs of concept to identify what is required to make them secure, maintainable and production-ready.
• Support other team members through technical guidance, code reviews and knowledge sharing. Governance & Best Practices
• Follow established ethical guidelines, data-protection requirements and internal governance policies.
• Maintain appropriate source-control, versioning (including prompts and configurations), testing and release standards.
• Document key technical decisions, risks and limitations, and contribute to reusable engineering standards and approved solution patterns. Documentation & Knowledge Sharing
• Maintain technical documentation for AI and automation solutions, including architecture diagrams, data flows, deployment instructions and operational runbooks.
• Document the Azure resources, identities, permissions and integrations a solution depends on, along with its data ingestion, retrieval and evaluation approach.
• Support the development of user guides and training materials, and share lessons learned through code reviews and technical walkthroughs. Principal Requirements Education
• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Cloud Computing or a related technical field.
• Advanced degrees or relevant Microsoft Azure certifications are an advantage. Experience
• At least 5 years’ experience in software development, AI engineering or a related technical role.
• Practical experience designing and delivering generative AI solutions, from business requirements to proof of concept through to production.
• Strong experience developing, deploying and supporting applications within Microsoft Azure, including secure or privately networked environments.
• Experience working with CI/CD pipelines, source control and controlled release processes.
• Experience working with enterprise IT, Cloud Platform or security teams, and taking technical ownership of application and deployment issues. Skills & Competencies Technical Expertise: AI
• Strong understanding of generative AI solution architectures and implementation patterns, including LLM applications, knowledge-grounded solutions, agentic AI, orchestration frameworks and AI-enabled automation.
• Hands-on experience designing, developing and deploying AI applications using Microsoft Foundry, Azure OpenAI, Azure AI Services and related technologies.
• Experience integrating AI solutions with enterprise knowledge sources, business systems, APIs and tools, including retrieval, search, grounding, reasoning, workflow orchestration and action execution capabilities where appropriate.
• Experience evaluating, testing and optimising AI solutions, including response quality, grounding, agent behaviour, reliability, performance, security and cost.
• Strong understanding of the security, governance, privacy and operational risks associated with generative and agentic AI, together with appropriate mitigation and control approaches. Technical Expertise: Azure
• Strong hands-on experience developing and deploying applications in Microsoft Azure, using services such as Azure Functions, App Service or Container Apps.
• Experience with Azure Storage, Key Vault, API Management, Cosmos DB and application-monitoring services.
• In-depth working knowledge of Azure networking as it affects application development (virtual networks, private endpoints, private DNS and restricted public access), sufficient to build and troubleshoot applications in private environments without needing to administer the network.
• Understanding of Microsoft Entra ID, managed identities and Azure role-based access control.
• Working knowledge of Git, Azure DevOps CI/CD pipelines and Docker; experience with Bicep, Terraform or another infrastructure-as-code technology is beneficial. Programming Skills
• Strong proficiency in Python.
• Experience developing backend services, integrating REST APIs and working with databases, search services and Azure resources.
• Understanding of secure application configuration, error handling, logging and dependency management.
• Experience with PowerShell, JavaScript, TypeScript or C# is beneficial. Technical Expertise: Automation
• Experience developing workflows using Microsoft Power Automate and the Power Platform, integrated with Microsoft 365, Azure services and external APIs.
• Familiarity with Power Apps and approval-based workflows is beneficial. Additional Competencies
• Strong technical problem-solving and troubleshooting skills.
• Ability to take ownership of complex solutions and work independently.
• Strong collaboration and communication skills, including the ability to explain technical architecture, risks and dependencies clearly.
• Practical understanding of security, governance and production-readiness requirements. Personal Attributes
• Technically strong: Brings practical experience and can take ownership of complex technical challenges.
• Delivery focused: Understands what is required to move a solution from proof of concept into secure and reliable production use.
• Security conscious: Considers access, data protection and operational risk from the beginning.
• Pragmatic: Selects technology based on the business requirement, risk, maintainability and cost.
• Collaborative communicator: Works effectively with business stakeholders, developers, IT, Cloud Platform and security teams, and explains technical decisions and risks clearly.
• Adaptable and curious: Keeps up with changes in AI and Azure while assessing new technologies carefully before adoption.