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.
Responsibilities
The Software Engineer will operate in a fast‑paced innovation environment, rapidly developing and validating proof‑of‑concepts for advanced AI and machine learning use cases. The role centers on experimenting with cutting‑edge analytics tools, integrating them into a cloud‑based analytics ecosystem, and helping move successful concepts toward operational deployment. Responsibilities include hands‑on data exploration, prototyping, workflow automation, and contributing to secure, well‑governed MLOps practices. The Software Engineer will work closely with engineering and product teams to evaluate emerging tools, build technical demonstrations, document integrations, and communicate platform updates in a highly collaborative setting. data platform fluency, and agility to support cross-functional teams.
Qualifications
5 years with BS/BA; 3 years with MS/MA; 0 years with PhD
Mandatory Requirements:
software engineering background with deep experience building production‑grade applications and services.
Expertise developing agentic AI systems, including planning, tool‑use, multi‑step reasoning, workflow execution, or autonomous decisioning logic.
Hands‑on experience designing and implementing MCP‑based integrations, tool interfaces, or model‑driven service frameworks.
Ability to translate ambiguous business or mission requirements into scalable AI-driven solutions, balancing technical feasibility with real-world impact.
Proficiency with LLM development practices including fine‑tuning, RAG integration, prompt engineering, and interaction models for agent workflows.
Strong Python development skills and familiarity with distributed compute environments, APIs, microservices, and cloud‑native architectures.
Experience integrating agents or LLM‑driven components into cloud platforms (Azure, AWS, GCP) or large‑scale data ecosystems.
Understanding of LLMOps/MLOps principles including versioning, testing, deployment automation, monitoring, and governance for agentic systems.
Demonstrated ability to lead solution design, mentor developers, and communicate complex AI architectures to technical and non‑technical stakeholders.
Experience with version control and modern CI/CD practices (e.g., Git/GitHub), including automated testing, deployment pipelines, and release management for production systems.
US Citizen with the ability to obtain/maintain a Public Trust clearance.
Preferred Requiremnts:
Experience building or contributing to multi‑agent systems or coordinated agent workflows.• Familiarity with frameworks such as LangChain, LlamaIndex, Strands Agents, LangGraph, CrewAI.
Knowledge of evaluating agent performance, implementing guardrails, or designing safe action‑execution patterns.
Hands‑on work with vector databases, embedding models, or advanced retrieval techniques.
Experience integrating agentic components into large‑scale analytics or data platforms (e.g., Databricks, Snowflake).
Background in data exploration or data modeling to support agent‑driven decision processes.
Experience building AI‑focused prototypes or experimenting with emerging agentic patterns in rapid‑iteration environments.
Familiarity with…