Software Engineer – AI Applications & ServiceNow

Deploy and operate applications within FedRAMP Moderate, FedRAMP High, and GCC High environments .

Engineer solutions in accordance with federal security requirements and organizational security architecture.

Support secure software development lifecycle (SSDLC) and DevSecOps practices, including automated build, test, security scanning, deployment, and release management.

Develop and maintain CI/CD pipelines supporting controlled application deployment across development, test, staging, and production environments.

Implement infrastructure-as-code and configuration-as-code practices where appropriate.

Support application security controls aligned with applicable frameworks such as NIST SP 800-53 and FedRAMP security control baselines .

Participate in vulnerability remediation, patching, configuration management, logging, monitoring, incident response, and operational troubleshooting.

Produce technical documentation and evidence supporting security assessments, Authorization to Operate (ATO) activities, configuration management, and operational readiness.

Engineer applications for high availability, reliability, scalability, maintainability, and secure operations.

Design, configure, develop, integrate, and maintain ServiceNow applications and workflows.

Develop ServiceNow solutions using capabilities such as:

Flow Designer

IntegrationHub

REST and SOAP APIs

Business Rules

Script Includes

Client Scripts

UI Policies

Access Control Lists (ACLs)

ServiceNow tables and data models

Notifications and workflow automation

Develop integrations between ServiceNow and external enterprise, cloud, security, data, and AI services.

Apply ServiceNow development best practices to create maintainable, secure, upgrade-compatible solutions.

Support troubleshooting, performance optimization, testing, release management, and ongoing maintenance of ServiceNow solutions.

Experience with ServiceNow AI, automation, ITSM, ITOM, CMDB, or related capabilities is highly desirable.

Bachelor's with 5 - 8 years (or commensurate experience)

Demonstrated professional software engineering experience developing and supporting enterprise applications.

Hands-on experience developing AI-enabled or generative AI applications suitable for production use.

Experience with modern programming languages such as Python, Java, JavaScript/TypeScript, C#, or comparable languages .

Experience developing RESTful APIs, microservices, web applications, or distributed application architectures.

Experience integrating applications with AI/ML services, LLMs, enterprise data sources, or external APIs.

Experience deploying, operating, troubleshooting, and maintaining applications in cloud environments.

Understanding of FedRAMP Moderate and/or FedRAMP High security requirements and experience working within regulated or security-controlled cloud environments.

Knowledge of secure software engineering, DevSecOps, CI/CD, source control, automated testing, vulnerability management, and production application support.

Experience engineering or supporting ServiceNow applications, integrations, workflows, or platform capabilities.

Strong understanding of application security principles including authentication, authorization, encryption, secrets management, secure APIs, logging, and auditing.

Ability to independently investigate complex technical problems and develop practical, secure solutions.

Strong written and verbal communication skills with the ability to document architectures, designs, interfaces, operational procedures, and technical decisions.

U.S. citizenship is required.

Must be able to obtain and maintain a U.S. Government Public Trust clearance .

Preferred Skills and Experience

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering , or a closely related technical discipline.

Experience working with Microsoft Azure Government and/or Microsoft GCC High environments .

Experience with Azure AI services, Azure OpenAI, or comparable government-authorized AI platforms.

Experience developing retrieval-augmented generation (RAG), semantic search, vector database, AI agent, or intelligent workflow solutions.

Experience implementing AI evaluation, observability, guardrails, model monitoring, prompt management, or responsible AI controls.

Experience with containerized applications and technologies such as Docker and Kubernetes.

Experience with infrastructure-as-code tools such as Terraform, Bicep, ARM templates, or equivalent technologies.

Experience supporting systems subject to NIST SP 800-53, FedRAMP, FISMA, or similar federal cybersecurity requirements .

Experience supporting ATO processes and producing technical or security documentation for government systems.

ServiceNow Certified System Administrator (CSA), Certified Application Developer (CAD), or other relevant ServiceNow certifications.

Experience with ServiceNow ITSM, ITOM, CMDB, IntegrationHub, App Engine, Now Assist, or related platform capabilities.

Experience working within Agile, Scrum, or DevSecOps delivery teams.

Experience supporting applications throughout the complete lifecycle from architecture and development through deployment, sustainment, modernization, and retirement.

Strong candidates will have experience across several of the following areas:

The successful candidate will be able to move comfortably between software engineering, AI engineering, ServiceNow development, cloud deployment, cybersecurity, and production operations . This individual will not simply develop prototypes; they will be expected to engineer solutions that can be securely deployed, accredited, operated, monitored, maintained, and continuously improved within demanding U.S. Government environments.

The ideal candidate is a pragmatic engineer who understands that successful enterprise AI requires more than model integration—it requires secure architecture, reliable software, governed data, operational discipline, effective monitoring, and maintainable engineering.

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