Application/Agentic AI Engineer

Responsibilities

• 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
• Train and mentor customer agent creators on Agent Builder workflows, publishing processes, testing methodologies, maintenance procedures, and operational best practices
• Develop reusable templates, workflow examples, implementation guides, and best-practice documentation to enable scalable and consistent customer development of agentic AI solutions
• Collaborate with cross-functional engineering, operations, cybersecurity, and product teams to ensure AI-enabled capabilities align with mission objectives, security requirements, and operational constraints
• Contribute to continuous improvement efforts for AI-enabled applications, orchestration frameworks, testing methodologies, and software delivery pipelines

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Systems, or related technical discipline
• 3+ years of experience in software engineering, application development, or AI/ML integration
• Experience developing applications using Python, JavaScript, TypeScript, Java, or similar modern programming languages
• Familiarity with Large Language Models (LLMs), prompt engineering, AI orchestration frameworks, or agentic AI concepts
• Experience with cloud-native technologies and containerized environments such as Docker and Kubernetes
• Understanding software development lifecycle (SDLC), DevSecOps, and CI/CD methodologies
• Experience with Git-based version control and collaborative development workflows
• Strong analytical, troubleshooting, and problem-solving skills
• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders

Desired Qualifications

• Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies
• Familiarity with AI model deployment, inference optimization, and scalable AI architecture
• Experience supporting government, defense, intelligence, or mission-focused environments
• Experience with AWS, Azure, or Google Cloud AI services
• Familiarity with cybersecurity best practices and secure software development
• Experience developing operational workflows using AI agents, automation pipelines, or decision-support systems