AI Software Engineer

We are seeking a Senior Full Stack Software Engineer to support a high-impact mission focused on AI-enabled software assurance, analytics, and emerging technology capabilities in a highly governed environment. This role blends hands-on full stack engineering (Java + Python) with practical AI/ML knowledge-especially around integrating modern AI services and building workflows that improve how teams analyze, certify, and secure software. You'll work directly with mission stakeholders to capture requirements, plan technical approaches, and deliver production-quality tools that streamline compliance, improve visibility, and enhance vulnerability identification and mitigation. The ideal candidate is comfortable operating in secure enclaves, building reliable systems end-to-end, and collaborating across engineering, security, and operations teams.

What You'll Do (Core Responsibilities)

Design, build, and maintain full stack applications that support mission workflows, reporting, and operational decision-making Develop and enhance backend services using Java (enterprise patterns, REST APIs, scalable services) Build supporting services, automation, and data-processing components using Python (pipelines, integrations, tooling, scripting) Collaborate with stakeholders to gather requirements, translate needs into technical designs, and deliver iterative functionality Create and maintain AI-assisted workflows that improve processes such as certification, compliance, testing, and vulnerability discovery Contribute to LLM-enabled solutions (e.g., retrieval-augmented approaches, prompt orchestration patterns, evaluation methods, or fine-tuning concepts) to help users find answers faster and identify risk more effectively Build and optimize data ingestion and preprocessing pipelines (ingest, clean, normalize, transform) to prepare artifacts such as documentation, code, and test results for analytics/AI consumption Design and implement storage solutions for:

Artifact repositories and audit trails Metadata management and traceability Relational and/or vector-friendly data access patterns supporting search and retrieval use cases

Integrate and operationalize AI capabilities via secure APIs (model endpoints, managed AI platforms, or approved AI gateways) within mission constraints Support deployment, performance profiling, reliability, and scalability of systems in restricted environments Participate in security assessments and support ATO-related engineering needs (documentation, traceability, operational readiness) Collaborate closely with cross-functional teams to drive teamwork, quality, and delivery outcomes

Java (senior-level, enterprise software engineering) Python (services, scripting, automation, data processing) Full stack experience building production applications (UI + APIs + data layer) Familiarity with AI/ML concepts and practical implementation patterns (e.g., LLM integration, RAG-style retrieval workflows, model evaluation, fine-tuning concepts, or orchestration patterns) Experience with Git-based workflows (GitLab preferred) including branching, merge requests, reviews, and CI habits Experience writing and consuming RESTful APIs and building service integration patterns Strong grasp of data engineering fundamentals (data quality, transformations, repeatable pipelines, and documentation) Ability to produce clear technical documentation (design notes, runbooks, workflow documentation, audit-friendly artifacts) Comfortable working in Agile delivery environments and collaborating using common planning/tracking tools Strong communication and teamwork skills in a mission-focused environment, Active Full Scope Polygraph (FS Poly) clearance Bachelor's degree plus 8+ years of relevant experience (or equivalent practical experience) Demonstrated ability to deliver complex software solutions end-to-end in highly regulated or security-conscious environments

Preferred / Nice-to-Have Skills

Experience with static analysis tools, automated testing pipelines, or software assurance workflows Familiarity with vector search concepts and/or systems used to support retrieval-heavy applications Experience deploying solutions into secure enclaves or restricted networks Containerization and platform experience (e.g., Docker, Kubernetes) CI/CD experience (build automation, test automation, release pipelines) Exposure to cloud-native patterns and services (compute, storage, messaging) in approved environments Familiarity with Rust Experience using modern AI development tooling (LLM coding assistants, prompt tooling, evaluation harnesses) Experience with analytics governance and AI governance approaches (model/data/workflow traceability, auditability, and policy alignment)

Work Environment

On-site work in a secure facility in Fort Meade, MD Highly collaborative team environment with strong mission alignment Emphasis on clean engineering practices, documentation, and repeatable delivery in a governed setting