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Second Front Systems

Managed DevSecOps SaaS for government software

AI Software Engineer

AI Application EngineeringUpdated on Nov 11
Full-timeRemote in USA

About the Job

Requirements

  • At least 2 years of full-time software, machine learning, or AI engineering experience, including hands-on production work building and shipping large language model-based systems.
  • Hands-on experience building agentic AI systems with tool-calling agents and multi-step orchestration using LangGraph, LangChain, or an equivalent technology.
  • Production experience with Retrieval-Augmented Generation, including vector stores, embedding models, chunking strategies, and retrieval quality optimization.
  • Experience deploying containerized AI services to cloud environments using Docker, Kubernetes (EKS preferred), and infrastructure as code (Terraform preferred).
  • Ability to communicate AI concepts and recommendations to non-technical stakeholders and cross-functional teams.
  • U.S. citizenship is required.
  • Candidates must reside in one of the approved hiring hubs: DC/Maryland/Virginia or Denver/Colorado Springs, Colorado.

Responsibilities

  • Architect production agentic AI systems using LangGraph and LangChain, focusing on reliability, traceability, and measurable output quality.
  • Build agent components, including ingestion pipelines, embedding strategies, chunking, retrieval, and re-ranking, and tool suites across managed knowledge-base services, vector databases, and internal and external APIs.
  • Connect agents to corporate tools and knowledge through Model Context Protocol by constructing MCP servers and consuming clients.
  • Establish and operate cloud infrastructure for R&D AI systems using Amazon EKS, Terraform, Helm, and GitOps delivery patterns.
  • Measure agent and large language model output quality through evaluation and regression suites covering groundedness, faithfulness, relevance, and retrieval quality, and run those suites in continuous integration.
  • Partner with Product teams to scope high-leverage AI opportunities across workflows and advise on agent design, model selection, and output quality standards.

Desired Qualifications

  • Experience building Model Context Protocol servers or clients, or integrating agents with enterprise tools and knowledge bases.
  • Experience with AWS AI services such as Bedrock Knowledge Bases, AgentCore, and OpenSearch.
  • Experience operating large language model gateways or serving infrastructure, such as LiteLLM, vLLM, or GPU-backed self-hosted models, including single- and multi-tenant designs.
  • Experience driving AI adoption across a product organization by enabling others to use AI effectively, beyond building AI systems.
  • Experience working in or with the Department of Defense, federal agencies, or regulated environments, and familiarity with compliance frameworks such as NIST 800-53, FedRAMP, or NATO D32.

About the Company

Second Front Systems

Managed DevSecOps SaaS for government software

Second Front Systems provides a subscription-based DevSecOps platform called Game Warden that helps U.S. government agencies and defense contractors deploy commercial software securely and compliantly. It acts as a fully managed service that handles security, operations, and ongoing compliance, and streamlines the Authorization to Operate (ATO) process so new SaaS products can be deployed faster. Unlike firms that only offer software, Second Front Systems focuses on bridging the commercial software market with national security needs by maintaining continuous updates and government-grade security across the software development lifecycle. The company’s goal is to enable rapid, secure, and compliant delivery of the latest commercial software to U.S. defense and homeland security missions.

Company size
51-200
Company stage
Series C
Total funding
$152.1M
Headquarters
Crystal City, Virginia
Founded
2014

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