Application Engineer, Agentic AI

Jobtailor

Aberdeen (MD)

On-site

USD 130,000 - 210,000

Full time

5 days ago

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Job summary

Jobtailor in Aberdeen, MD seeks an experienced software engineer to translate mission workflows into agentic AI solutions and maintain agent definitions, safety policies, and tool-use rules. You will design reusable AI patterns and orchestration workflows for enterprise use.

You will build and run AI testing suites, analyze failures, and integrate AI agents into existing applications, following DevSecOps practices across cloud, edge, and hybrid environments.

Qualifications

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.
Experience integrating APIs, microservices, and data services into enterprise or operational applications.
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.
Active Security Clearance is required.
Desired: Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies
Desired: Familiarity with AI model deployment, inference optimization, and scalable AI architecture
Desired: Experience supporting government, defense, intelligence, or mission-focused environments
Desired: Experience with AWS, Azure, or Google Cloud AI services
Desired: Familiarity with cybersecurity best practices and secure software development
Desired: Experience developing operational workflows using AI agents, automation pipelines, or decision-support systems

Responsibilities

Translate mission workflows and operational requirements into agentic AI solutions with intelligent agents and tooling
Design, develop, and maintain agent definitions, objectives, and safety policies
Develop workflow-specific AI specialists and reusable agent patterns
Build AI testing and evaluation suites, including validation and adversarial testing
Analyze failed or degraded agent tests to improve performance
Integrate AI agents and services into applications following DevSecOps practices
Support deployment and sustainment of AI-enabled workflows across cloud/edge/hybrid environments
Train customer agents on Builder workflows, testing and maintenance
Develop reusable templates, guides, and best-practice documentation
Collaborate with engineering, security, and product teams to align AI capabilities with objectives
Contribute to continuous improvement of AI applications and delivery pipelines

Skills

Python Development

AI Orchestration Frameworks

Cloud-native Technologies

DevSecOps Practices

Active Security Clearance

Education

Bachelor's degree in Computer Science

Tools

Docker

Kubernetes

AWS

Azure

Google Cloud AI Services

Job description

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 for operational and enterprise use cases
Build and maintain AI testing and evaluation suites, including 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
Integrate AI agents, orchestration workflows, APIs, and supporting services into existing applications using software engineering and DevSecOps practices
Support 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, testing, maintenance, and operational best practices
Develop reusable templates, workflow examples, implementation guides, and best-practice documentation
Collaborate with engineering, operations, cybersecurity, and product teams to align AI capabilities with mission objectives, security requirements, and operational constraints
Contribute to continuous improvement of AI 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
Experience integrating APIs, microservices, and data services into enterprise or operational applications
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
Active Security Clearance is required
Desired: Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies
Desired: Familiarity with AI model deployment, inference optimization, and scalable AI architecture
Desired: Experience supporting government, defense, intelligence, or mission-focused environments
Desired: Experience with AWS, Azure, or Google Cloud AI services
Desired: Familiarity with cybersecurity best practices and secure software development
Desired: Experience developing operational workflows using AI agents, automation pipelines, or decision-support systems

Core Competencies

Demonstrates expertise in developing and integrating AI solutions, including agentic AI and orchestration frameworks, while effectively communicating technical concepts to diverse stakeholders. Proficient in software engineering practices, cloud-native technologies, and AI testing methodologies.

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