Peraton is seeking an AI Application Developer to design and build production-grade AI systems and lead the next evolution of software delivery across Government (Federal State and Local) programs by operationalizing AI at scale. This role is focused on embedding AI across the Software Development Life Cycle (SDLC) focused on LLM integration agent-based systems and AI-native software engineering DevSecOps with AI transforming how systems are built tested secured and operated via AI driven development.
You will design and implement AI-orchestrated agent-driven workflows leveraging cloud-native platforms and secure government AI environments (including ). The objective is to move beyond isolated AI use cases and deliver repeatable governed and measurable AI-enabled systems that accelerate delivery to scalable mission-ready AI solutions. This is an engineer role for someone who understands that real impact comes from orchestrating models data and workflows into production-grade capabilities.
Location: Candidate must be local to the Columbus Ohio area.
What Youll Do
Architect and implement AI-enabled solutions that accelerate code generation testing security documentation and deployment
Design and build LLM-powered applications and agentic systems for software development testing security and operations
Design and operationalize agentic multi-step workflows (e.g. code test validate deploy) with appropriate human-in-the-loop controls
Leverage and integrate models and commercial LLMs with cloud-native AI services into secure scalable development environments
Build and integrate AI microservices and APIs into cloud-native platforms
Build future-state architecture and data pipelines that ground AI outputs in authoritative mission-relevant data
Establish prompt frameworks chaining strategies and reusable AI patterns that scale across teams and programs
Integrate AI into IT operations (ticket triage root cause analysis observability incident response) to enable closed-loop automation
Define and track performance metrics (cycle time defect reduction cost-per-feature SLA improvements) tied to AI adoption
Lead technical adoption across teams mentoring engineers and standardizing best practices
Ensure compliance with federal security data governance and AI usage policies
Implement RAG architectures using mission data (codebases documentation operational data) to ground AI outputs
Critical Skills: AI Orchestration & Systems Thinking
LLM & Agentic Workflow Development
Design and implement multi-agent orchestration tool integration and workflow automation with tool use memory and feedback loops
Balance automation control and reliability in mission-critical environments
Prompt engineering prompt chaining and reusable prompt architectures
Evaluation frameworks for output quality reliability and drift
Data & Retrieval Strategy
Build and optimize RAG architectures and secure data access patterns
Structure and govern data (codebases runbooks tickets documentation) for effective AI consumption
Design build and maintain Vector databases and semantic search
Ensure data lineage integrity secure access patterns and classification compliance
Model & Platform Orchestration
Orchestrate across multiple models and endpoints including
Implement routing fallback and optimization strategies based on latency cost and accuracy
Design for secure compliant AI usage in federal environments
Implement evaluation pipelines to measure output quality drift and reliability
Ensure outputs are traceable testable and auditable
AI-Enabled DevSecOps SDLC & AIOps
Embed AI into CI/CD security scanning testing and documentation workflows
Apply AI to operations (incident response anomaly detection automated remediation)
Enable closed-loop systems (detect decide act)
AI-assisted SDLC development workflows and pipeline integration (code test security documentation)
Observability Metrics & Governance
Define KPIs tied to AI-driven performance gains
Implement monitoring for AI system behavior cost and outcomes
Align with DoD/DHA governance security and compliance frameworks
What Success Looks Like
2040% improvements in in SDLC cycle time through AI-enabled workflows
Deliver production-grade AI applications and agentic workflows deployed in secure environments
Improve code quality operational efficiency and system resilience using AI
Standardized reusable AI orchestration patterns deployed across programs
Measurable improvements in SLA performance cost efficiency and mission delivery speed
Qualifications
Required Qualifications
Minimum of 2 years of experience with BA/BS; Preferable in software engineering DevSecOps platform engineering or related field
Minimum of 2 years of hands-on experience building AI/LLM-based applications or workflows
Demonstrated experience integrating AI/LLM-based capabilities into engineering or operational workflows
Experience with LLM frameworks and orchestration tools (e.g. LangChain LlamaIndex AutoGen CrewAI or similar)
Strong expertise in cloud-native architectures (AWS Azure or GCP)
Deep understanding of CI/CD pipelines DevSecOps practices and modern SDLC frameworks
Strong program skills in in Python and at least one additional language (Java JavaScript Go etc.)
Experience designing and deploying distributed systems APIs and microservices-based architectures
U.S. Citizenship
Ability to obtain Public Trust Clearance (potential to obtain Secret Clearance)
Preferred Qualifications
Preferred 2-5 years of hands on experience developing and maintainingAI Platforms
Direct experience with or other secure government AI platforms
Expertise in agent frameworks LLM orchestration or emerging AI workflow tooling
Experience with Kubernetes containerized environments and platform engineering
Familiarity with MLOps AIOps or AI governance frameworks
Experience supporting DoD DHA or federal health systems (e.g. MHS GENESIS)
Experience deploying AI solutions in IL4/IL5 or FedRAMP High environments
Active TS/SCI clearance
Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the worlds leading mission capability integrator and transformative enterprise IT provider we deliver trusted highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land sea space air and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day our employees do the cant be done by solving the most daunting challenges facing our customers. Visit to learn how were keeping people around the world safe and secure.
Target Salary Range
$86000 - $138000. This represents the typical salary range for this position. Salary is determined by various factors including but not limited to the scope and responsibilities of the position the individuals experience education knowledge skills and competencies as well as geographic location and business and contract considerations. Depending on the position employees may be eligible for overtime shift differential and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer including disability and protected veterans or other characteristics protected by law.
Required Experience:
IC
ResponsibilitiesPeraton is seeking an AI Application Developer to design and build production-grade AI systems and lead the next evolution of software delivery across Government (Federal State and Local) programs by operationalizing AI at scale. This role is focused on embedding AI across the Softwa...
Responsibilities
Peraton is seeking an AI Application Developer to design and build production-grade AI systems and lead the next evolution of software delivery across Government (Federal State and Local) programs by operationalizing AI at scale. This role is focused on embedding AI across the Software Development Life Cycle (SDLC) focused on LLM integration agent-based systems and AI-native software engineering DevSecOps with AI transforming how systems are built tested secured and operated via AI driven development.
You will design and implement AI-orchestrated agent-driven workflows leveraging cloud-native platforms and secure government AI environments (including ). The objective is to move beyond isolated AI use cases and deliver repeatable governed and measurable AI-enabled systems that accelerate delivery to scalable mission-ready AI solutions. This is an engineer role for someone who understands that real impact comes from orchestrating models data and workflows into production-grade capabilities.
Location: Candidate must be local to the Columbus Ohio area.
What Youll Do
Architect and implement AI-enabled solutions that accelerate code generation testing security documentation and deployment
Design and build LLM-powered applications and agentic systems for software development testing security and operations
Design and operationalize agentic multi-step workflows (e.g. code test validate deploy) with appropriate human-in-the-loop controls
Leverage and integrate models and commercial LLMs with cloud-native AI services into secure scalable development environments
Build and integrate AI microservices and APIs into cloud-native platforms
Build future-state architecture and data pipelines that ground AI outputs in authoritative mission-relevant data
Establish prompt frameworks chaining strategies and reusable AI patterns that scale across teams and programs
Integrate AI into IT operations (ticket triage root cause analysis observability incident response) to enable closed-loop automation
Define and track performance metrics (cycle time defect reduction cost-per-feature SLA improvements) tied to AI adoption
Lead technical adoption across teams mentoring engineers and standardizing best practices
Ensure compliance with federal security data governance and AI usage policies
Implement RAG architectures using mission data (codebases documentation operational data) to ground AI outputs
Critical Skills: AI Orchestration & Systems Thinking
LLM & Agentic Workflow Development
Design and implement multi-agent orchestration tool integration and workflow automation with tool use memory and feedback loops
Balance automation control and reliability in mission-critical environments
Prompt engineering prompt chaining and reusable prompt architectures
Evaluation frameworks for output quality reliability and drift
Data & Retrieval Strategy
Build and optimize RAG architectures and secure data access patterns
Structure and govern data (codebases runbooks tickets documentation) for effective AI consumption
Design build and maintain Vector databases and semantic search
Ensure data lineage integrity secure access patterns and classification compliance
Model & Platform Orchestration
Orchestrate across multiple models and endpoints including
Implement routing fallback and optimization strategies based on latency cost and accuracy
Design for secure compliant AI usage in federal environments
Implement evaluation pipelines to measure output quality drift and reliability
Ensure outputs are traceable testable and auditable
AI-Enabled DevSecOps SDLC & AIOps
Embed AI into CI/CD security scanning testing and documentation workflows
Apply AI to operations (incident response anomaly detection automated remediation)
Enable closed-loop systems (detect decide act)
AI-assisted SDLC development workflows and pipeline integration (code test security documentation)
Observability Metrics & Governance
Define KPIs tied to AI-driven performance gains
Implement monitoring for AI system behavior cost and outcomes
Align with DoD/DHA governance security and compliance frameworks
What Success Looks Like
2040% improvements in in SDLC cycle time through AI-enabled workflows
Deliver production-grade AI applications and agentic workflows deployed in secure environments
Improve code quality operational efficiency and system resilience using AI
Standardized reusable AI orchestration patterns deployed across programs
Measurable improvements in SLA performance cost efficiency and mission delivery speed
Qualifications
Required Qualifications
Minimum of 2 years of experience with BA/BS; Preferable in software engineering DevSecOps platform engineering or related field
Minimum of 2 years of hands-on experience building AI/LLM-based applications or workflows
Demonstrated experience integrating AI/LLM-based capabilities into engineering or operational workflows
Experience with LLM frameworks and orchestration tools (e.g. LangChain LlamaIndex AutoGen CrewAI or similar)
Strong expertise in cloud-native architectures (AWS Azure or GCP)
Deep understanding of CI/CD pipelines DevSecOps practices and modern SDLC frameworks
Strong program skills in in Python and at least one additional language (Java JavaScript Go etc.)
Experience designing and deploying distributed systems APIs and microservices-based architectures
U.S. Citizenship
Ability to obtain Public Trust Clearance (potential to obtain Secret Clearance)
Preferred Qualifications
Preferred 2-5 years of hands on experience developing and maintainingAI Platforms
Direct experience with or other secure government AI platforms
Expertise in agent frameworks LLM orchestration or emerging AI workflow tooling
Experience with Kubernetes containerized environments and platform engineering
Familiarity with MLOps AIOps or AI governance frameworks
Experience supporting DoD DHA or federal health systems (e.g. MHS GENESIS)
Experience deploying AI solutions in IL4/IL5 or FedRAMP High environments
Active TS/SCI clearance
Peraton Overview
Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the worlds leading mission capability integrator and transformative enterprise IT provider we deliver trusted highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land sea space air and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day our employees do the cant be done by solving the most daunting challenges facing our customers. Visit to learn how were keeping people around the world safe and secure.
Target Salary Range
$86000 - $138000. This represents the typical salary range for this position. Salary is determined by various factors including but not limited to the scope and responsibilities of the position the individuals experience education knowledge skills and competencies as well as geographic location and business and contract considerations. Depending on the position employees may be eligible for overtime shift differential and a discretionary bonus in addition to base pay.
EEO
EEO: Equal opportunity employer including disability and protected veterans or other characteristics protected by law.
Peraton provides innovative solutions for the most sensitive and critical programs in government today, developed and executed by scientists, engineers, and other experts.
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