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You will design and implement AI-orchestrated, agent-driven workflows leveraging cloud-native platforms and secure government AI environments (including GenAI.mil). The objective is to move beyond isolated AI use cases and deliver repeatable, governed, and measurable AI-enabled systems that accelerate delivery of to scalable, mission-ready AI solutions.
This is a engineer role for someone who understands that real impact comes from orchestrating models, data, and workflows into production-grade capabilities.
This position will report to Reston, VA with occastional telework options.
What You'll DoArchitect and implement AI-enabled DevSecOps pipelines that accelerate code generation, testing, security, documentation, and deploymentDesign and build LLM-powered applications and agentic systems for software development, testing, security, and operationsDesign and operationalize agentic, multi-step workflows (e.g., code test validate deploy) with appropriate human-in-the-loop controlsLeverage and integrate GenAI.mil models and commercial LLMs with cloud-native AI services into secure, scalable development environmentsBuild and integrate AI microservices and APIs into cloud-native platformsBuild future-state architecture and data pipelines that ground AI outputs in authoritative, mission-relevant dataEstablish prompt frameworks, chaining strategies and reusable AI patterns that scale across teams and programsIntegrate AI into IT operations (ticket triage, root cause analysis, observability, incident response) to enable closed-loop automationDefine and track performance metrics (cycle time, defect reduction, cost-per-feature, SLA improvements) tied to AI adoptionLead technical adoption across teams, mentoring engineers and standardizing best practicesEnsure compliance with federal security, data governance, and AI usage policiesImplement RAG architectures using mission data (codebases, documentation, operational data) to ground AI outputs
Target Salary Range$112,000 - $179,000. 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 individual's 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.
PC
Peraton Corporation
Senior AI Engineer
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$124,809 / year median in Virginia
Job Description
Senior AI Engineer Company:
Peraton Corporation Location:
Reston, VA, 20190Posted:
August 27, 2026 Apply ⚑ Report jobDescription:
ResponsibilitiesOverviewPeraton is seeking a Senior AI Engineer to to design and build production-grade AI systems and lead the next evolution of software delivery across Defense & Health 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 GenAI.mil). The objective is to move beyond isolated AI use cases and deliver repeatable, governed, and measurable AI-enabled systems that accelerate delivery of to scalable, mission-ready AI solutions.
This is a engineer role for someone who understands that real impact comes from orchestrating models, data, and workflows into production-grade capabilities.
This position will report to Reston, VA with occastional telework options.
What You'll DoArchitect and implement AI-enabled DevSecOps pipelines that accelerate code generation, testing, security, documentation, and deploymentDesign and build LLM-powered applications and agentic systems for software development, testing, security, and operationsDesign and operationalize agentic, multi-step workflows (e.g., code test validate deploy) with appropriate human-in-the-loop controlsLeverage and integrate GenAI.mil models and commercial LLMs with cloud-native AI services into secure, scalable development environmentsBuild and integrate AI microservices and APIs into cloud-native platformsBuild future-state architecture and data pipelines that ground AI outputs in authoritative, mission-relevant dataEstablish prompt frameworks, chaining strategies and reusable AI patterns that scale across teams and programsIntegrate AI into IT operations (ticket triage, root cause analysis, observability, incident response) to enable closed-loop automationDefine and track performance metrics (cycle time, defect reduction, cost-per-feature, SLA improvements) tied to AI adoptionLead technical adoption across teams, mentoring engineers and standardizing best practicesEnsure compliance with federal security, data governance, and AI usage policiesImplement RAG architectures using mission data (codebases, documentation, operational data) to ground AI outputs
Critical Skills:
AI Orchestration & Systems ThinkingLLM & Agentic Workflow DevelopmentDesign and implement multi-agent orchestration, tool integration and workflow automation with tool use, memory, and feedback loopsBalance automation, control, and reliability in mission-critical environmentsPrompt engineering, prompt chaining, and reusable prompt architecturesEvaluation frameworks for output quality, reliability, and driftData & Retrieval StrategyBuild and optimize RAG architectures and secure data access patternsStructure and govern data (codebases, runbooks, tickets, documentation) for effective AI consumptionDesign, build and maintain Vector databases and semantic searchEnsure data lineage, integrity, secure access patterns and classification complianceModel & Platform OrchestrationOrchestrate across multiple models and endpoints, including GenAI.milImplement routing, fallback, and optimization strategies based on latency, cost, and accuracyDesign for secure, compliant AI usage in federal environmentsPrompt Systems & EvaluationDevelop scalable prompt frameworks (templates, chaining, reuse)Implement evaluation pipelines to measure output quality, drift, and reliabilityEnsure outputs are traceable, testable, and auditableAI-Enabled DevSecOps, SDLC & AIOpsEmbed AI into CI/CD, security scanning, testing, and documentation workflowsApply AI to operations (incident response, anomaly detection, automated remediation)Enable closed-loop systems (detect decide act)AI-assisted SDLCdevelopment workflows and pipeline integration (code, test, security, documentation)Observability, Metrics & GovernanceDefine KPIs tied to AI-driven performance gainsImplement monitoring for AI system behavior, cost, and outcomesAlign with DoD/DHA governance, security, and compliance frameworksWhat Success Looks Like20-40% improvements in in SDLC cycle time through AI-enabled workflowsDeliver production-grade AI applications and agentic workflows deployed in secure environmentsImprove code quality, operational efficiency, and system resilience using AIStandardized, reusable AI orchestration patterns deployed across programsMeasurable improvements in SLA performance, cost efficiency, and mission delivery speedQualificationsRequired QualificationsUS CitizenshipActive Secret clearance 5 years with BS/BA5-10+ years of experience in software engineering, DevSecOps, platform engineering, or related field2+ years of hands-on experience building AI/LLM-based applications or workflowsDemonstrated experience integrating AI/LLM-based capabilities into engineering or operational workflowsExperience 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 frameworksStrong 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 architecturesPreferred QualificationsDirect experience with GenAI.mil or other secure government AI platformsExpertise in agent frameworks, LLM orchestration, or emerging AI workflow toolingExperience with Kubernetes, containerized environments, and platform engineeringFamiliarity with MLOps, AIOps, or AI governance frameworksExperience supporting DoD, DHA, or federal health systems (e.g., MHS GENESIS)Experience deploying AI solutions in IL4/IL5 or FedRAMP High environmentsActive TS/SCI clearancePeraton OverviewPeraton 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 world's 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 can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.Target Salary Range$112,000 - $179,000. 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 individual's 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.