Principal Software Engineer

Location: Fairfax, VA
Please note: This position is subject to pre-employment criminal and credit background checks.

The National Rifle Association is executing a major greenfield AI-first digital transformation to design and build sovereign, intelligent platforms that drive member engagement, data-driven growth, and operational excellence.

We are seeking a deeply technical Principal Software Engineer / Technical Lead - a senior individual contributor who writes high-impact production code daily while leading the delivery of durable application-tier services and advanced data intelligence capabilities. Reporting to the Senior Director of Enterprise Architecture & Software Engineering, this role owns the creation of production AI systems, graph/vector knowledge platforms, and analytics solutions that translate raw data into actionable business intelligence.

This position operates at principal/staff engineer level: providing technical direction, owning complex systems end-to-end, and delivering capabilities that directly enable revenue, membership growth, and mission-aligned outcomes.

Key Responsibilities

Architecture & Durable System Design:
Design and implement resilient, production-grade application services using modern frameworks (Spring Boot/Java ecosystems or equivalents such as Quarkus/Micronaut, alongside Python FastAPI).
Own end-to-end development of scalable microservices, event-driven architectures, API/MCP-first platforms, and domain-driven designs that serve as the durable foundation for long-term capabilities.
Architect and build sophisticated multi-agent systems, LLM orchestration, Retrieval-Augmented Generation (RAG), vector databases, and graph database solutions that power intelligent decision-making.

Data Intelligence & Analytics Leadership
Lead the delivery of data intelligence platforms that unify member and operational data into actionable insights, leveraging graph databases for relationship modeling, vector stores for semantic search, and AI agents for automated analysis and recommendations.
Design and implement real-time analytics pipelines, predictive models, knowledge graphs, and intelligent profiling systems that directly enable business capabilities such as personalized member experiences, donor segmentation, churn prediction, and revenue optimization.
Translate complex business requirements into production data intelligence features that drive measurable outcomes across membership, advancement, digital engagement, and operations.

API & Integration Leadership
Design, implement, and govern robust internal and external APIs, integration platforms, and secure partner connectivity solutions.
Build integration layers that support seamless data flow and workflow orchestration between internal systems and external partners.

Code Ownership & Technical Excellence
Write high-quality, daily production code primarily in Python and TypeScript/Java, focusing on performance, reliability, and maintainability.
Drive engineering standards, conduct rigorous code and design reviews, and establish patterns for testing, observability, and operational excellence.
Implement mature MLOps/LLMOps, Infrastructure-as-Code, GitOps, and CI/CD practices.
Optimize high-throughput AI and data workloads for scalability, latency, and cost efficiency.

AI-Native & Agentic Development
Build production-grade agentic systems capable of complex reasoning, tool use, and autonomous execution across data intelligence workflows.
Productionize advanced AI components including embeddings, knowledge graphs, prompt engineering, and responsible AI safeguards.

Influence & Mentorship
Provide technical leadership and mentorship across teams, raising the bar on AI engineering, data intelligence, and cloud-native practices.
Collaborate with architecture, security, and business stakeholders to ensure technical solutions deliver clear business value.
Contribute to technical roadmaps and platform strategy.

Security, Compliance & Operational Excellence
Embed zero-trust security, privacy-by-design, data sovereignty, and AI Governance into all layers.
Drive technical debt reduction, platform reliability, and cost optimization while maintaining rigorous compliance standards.

Qualifications & Experience
Required:
8+ years of hands-on production software engineering experience, with significant time at senior/principal level building large-scale, mission-critical systems.
Demonstrated expertise designing and owning durable application-tier services (Spring Boot/Java or equivalent) combined with Python/TypeScript AI-native development.
Strong track record in the following areas:
App Tier & Backend: Spring Boot (or Quarkus/Micronaut), Python (FastAPI, LangChain/LangGraph/CrewAI), TypeScript/Node.js, focused on high-throughput, observable services.
Data Intelligence: Graph databases (Neo4j, FalkorDB), vector databases (e.g. Pinecone, Weaviate, Qdrant), knowledge graphs, real-time analytics pipelines, predictive modeling, and semantic search.
AI/ML Engineering: Multi-agent systems, LLM orchestration, RAG architectures, agentic frameworks, and MLOps/LLMOps.
Cloud & Architecture: AWS/Azure/GCP, Kubernetes, event-driven systems (Kafka/Pulsar), serverless, API gateways, domain-driven design, and partner integrations.
Deep experience designing secure, scalable APIs and integration platforms.
Expertise with Infrastructure-as-Code, GitOps, comprehensive observability, and automated quality practices.
Proven success applying zero-trust security, data sovereignty, and AI Governance in production.
Ability to deliver measurable business impact through hands-on technical leadership in data intelligence and AI systems.
Support and alignment to the mission, values, and culture of the NRA. Salary is budgeted as $120,000 to $175,000/year, DOQ

Preferred:
Experience building intelligent platforms for membership, e-commerce, or high-engagement consumer applications.
Contributions to open-source AI/data projects, technical blogs, or conference speaking.
Familiarity with Microsoft Azure services in a multi-cloud strategy. Relevant certifications: AWS/Azure Architect/Developer, CKA/CKAD, or AI/ML engineering credentials.

Education: Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, Data Science, or related field (or equivalent deep professional experience).