AI Software Engineer

Second Front Systems

. Architect production agentic AI systems using LangGraph and LangChain, focusing on reliability, traceability, and measurable output quality .

Posted 10/27/2026full-timeRemote • United StatesJuniorMid-Level💰 $150,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and deploying agentic AI systems, with a strong focus on reliability, traceability, and measurable output quality. Proficient in building and integrating AI components, cloud infrastructure, and communicating complex AI concepts to diverse stakeholders.

Highest-signal resume keywords

LangGraph ExperienceLangChain ExperienceRetrieval-Augmented GenerationDocker and Kubernetes DeploymentAWS AI Services Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI EngineeringProduction AI SystemsAgentic AI SystemsEmbedding ModelsChunking StrategiesRetrieval Quality OptimizationInfrastructure as CodeCloud InfrastructureCI Evaluation SuitesMCP Server Development

Soft Skills

Communication with Non-Technical StakeholdersCross-Functional Team Collaboration

Tools & Technologies

Amazon EKSTerraformHelmDockerKubernetesVector DatabasesKnowledge Base ServicesGitOpsOpenSearchLiteLLM

Industry Keywords

National SecurityRegulated NetworksDepartment of DefenseNIST 800-53FedRAMPNATO D32

Tech Stack

Tools & technologies

AWSCloudDockerKubernetesTerraform

About the role

Key responsibilities & impact

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
Build 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, 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 LLM output quality through evaluation and regression suites covering groundedness, faithfulness, relevance, and retrieval quality, running in CI
Partner with Product teams to scope high-leverage AI opportunities across workflows
Advise on agent design, model selection, implementation, responsible AI governance, and output quality standards
Build documentation and reusable components that expand organizational AI capability
Translate research-grade AI systems into mission-ready products for national security and regulated networks

Requirements

What you’ll need

2+ years full-time software, ML, or AI engineering experience with hands-on production work building and shipping LLM-based systems
Hands-on experience building agentic AI systems with tool-calling agents and multi-step orchestration using LangGraph, LangChain, or equivalent
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)
Demonstrated ability to communicate AI concepts and recommendations to non-technical stakeholders and cross-functional teams
U.S. citizenship and residence in an approved hiring hub: DC/Maryland/Virginia; Raleigh/Durham/Chapel Hill, NC; Denver/Colorado Springs, CO; or Dallas/Fort Worth, TX
Preferred: experience building MCP servers or clients, or integrating agents with enterprise tools and knowledge bases
Preferred: experience with AWS AI services such as Bedrock Knowledge Bases, AgentCore, and OpenSearch
Preferred: experience operating LLM gateways or serving infrastructure such as LiteLLM, vLLM, and GPU-backed self-hosted models, including single- and multi-tenant designs
Preferred: experience driving AI adoption across a product organization
Preferred: experience working in or with the Department of Defense, federal agencies, or regulated environments
Preferred: familiarity with NIST 800-53, FedRAMP, or NATO D32
Must be able to work in the United States; application asks whether the candidate currently obtains a security clearance

Benefits

Comp & perks

Potential eligibility for equity awards
Discretionary bonuses
100% employer-paid medical, dental, and vision coverage for you and your dependents
401(k) with a 3% company contribution
Comprehensive wellness benefits, including a One Medical membership, mental health resources, family planning support, and more
Equity incentive plan
New hire technology and home office stipend
Annual professional development stipend
Flexible paid time off, plus all federal holidays
Generous parental leave
Flexible remote work opportunities
Employee referral bonus program