AI Application Developer

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 GenAI.mil). 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 You'll 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 GenAI.mil 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 GenAI.mil

Implement routing, fallback, and optimization strategies based on latency, cost, and accuracy

Design for secure, compliant AI usage in federal environments

Prompt Systems & Evaluation

Develop scalable prompt frameworks (templates, chaining, reuse)

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

20–40% 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 maintaining AI Platforms

Direct experience with GenAI.mil 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 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

$86,000 - $138,000. 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.

EEO

EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.