Application / Agentic AI Engineer

NextGen is seeking a highly motivated and technically skilled Application/Agentic AI Engineer to support the integration, and deployment of modern AI-enabled applications and agentic AI capabilities in support of mission objectives using ReadiChat.

ReadiChat is a mission-focused, agentic AI platform designed to help organizations build, deploy, govern, and scale specialized AI agents for operational workflows.

It combines AI agents, workflow orchestration, grounded knowledge, testing frameworks, and enterprise controls into a single collaborative workspace.

The selected candidate will work across software engineering, AI/ML integration, workflow orchestration, and operational problem-solving to develop intelligent systems that improve decision-making, automation, and user interaction in complex environments.

This role requires a blend of software engineering expertise, AI integration experience, systems thinking, and the ability to collaborate directly with operational users, engineers, and program stakeholders to translate mission requirements into scalable AI-enabled solutions.

• Partner with customer SMEs and operational stakeholders to translate mission workflows and operational requirements into agentic AI solutions, including intelligent agents, workflow specialists, guardrails, tools, and validation frameworks.
• Design, develop, and maintain agent definitions and configurations, including objectives, behavioral instructions, input/output contracts, safety policies, operational constraints, and tool utilization rules.
• Develop workflow-specific AI specialists and reusable agent patterns to support operational and enterprise use cases while maintaining clear functional boundaries and scalable architectures.
• Build and maintain comprehensive AI testing and evaluation suites, including gold-standard input/output validation, adversarial testing, guardrail validation, scope-boundary testing, tool-use validation, regression testing, and multi-turn conversational testing.
• Analyze failed, degraded, or stale agent test results to identify performance gaps, tune agent behavior, improve reliability, and document updates across agent versions and releases.
• Integrate AI agents, orchestration workflows, APIs, and supporting services into existing application and operational environments using modern software engineering and DevSecOps practices.
• Support the deployment, sustainment, troubleshooting, and optimization of AI-enabled applications and agentic workflows across cloud, edge, and hybrid environments.