Senior Python Developer

Take on a senior engineering role at the intersection of cybersecurity, Python development, and artificial intelligence. You’ll help advance a security compliance platform designed to support complex government and defense environments. Combining scalable security automation with production-ready AI capabilities, you’ll build solutions that improve how cybersecurity requirements are processed, validated, and operationalized. You’ll work with both locally hosted and cloud-based AI models, developing reliable systems for connected, restricted, and air-gapped environments. This remote opportunity offers significant technical ownership, architectural influence, and the chance to mentor developers while delivering secure, mission-critical software.

• Bachelor’s degree in computer science, software engineering, data science, AI/ML, or a related field. Relevant professional experience may be considered in place of a degree.

• At least 8 years of relevant professional experience, including a minimum of 4 years of professional Python software development.

• Demonstrated experience designing, developing, testing, deploying, and operating production Python software and AI-enabled applications.

• Hands-on experience integrating local or self-hosted AI/large language models (LLMs), cloud-hosted AI services, or model APIs.

• Practical knowledge of AI/ML techniques, including data preparation, model training concepts, model selection, validation, evaluation, inference, and model adaptation.

• Experience applying AI to automate complex business, engineering, or analytical workflows with measurable operational impact.

• Experience developing distributed data-collection systems or comparable software, with an understanding of performance, reliability, concurrency, and large-scale deployment across segmented or federated networks.

• Strong knowledge of software engineering principles, network architectures, cybersecurity technologies, and regulatory or compliance requirements.

• Understanding of prompting, retrieval-augmented generation (RAG), fine-tuning, and other approaches for determining whether AI models are suitable for production use cases.

• Familiarity with workflow automation, intelligent document processing, data extraction, validation methodologies, and human-in-the-loop review.

• Ability to evaluate the trade-offs between local inference and cloud models, including security boundaries, latency, cost, model capabilities, and disconnected deployment environments.

• Strong analytical and problem-solving skills, sound technical judgment, and the ability to analyze existing codebases and make architectural decisions independently.

• Effective communication, organizational, and project management skills, with the ability to manage competing priorities and meet deadlines.

• Ability to work collaboratively with technical teams, leadership, customers, and external stakeholders while handling confidential information appropriately.

• U.S. citizenship and the ability to pass pre-employment background screening and obtain and maintain a security clearance.

• Willingness and ability to travel up to 10%.

Preferred qualifications:

• Active Secret or Top Secret security clearance.

• Experience with DISA STIGs, SCAP content, or comparable cybersecurity compliance frameworks.

• Experience developing or deploying software in Department of Defense or other federal environments, particularly restricted, air-gapped, disconnected, or accreditation-controlled networks.

• Familiarity with RAG, embeddings, vector databases, structured outputs, tool or function calling, document parsing, information extraction, agentic workflows, and AI evaluation frameworks.

• Experience deploying and optimizing local or self-hosted models in restricted or resource-constrained environments, including model serving, quantization, and GPU/CPU performance trade-offs.

• Hands-on experience with cloud AI platforms and hosted model services, such as Azure OpenAI, AWS Bedrock, OpenAI APIs, or Google Vertex AI.

• Experience with model and version management, evaluation pipelines, experiment tracking, monitoring, quality controls, and production governance for AI-enabled software.

• Experience leading development teams through task assignment, architecture and code reviews, mentoring, and stakeholder coordination.

• Experience contributing to enterprise dashboards and full-stack web applications, including reporting, visualization, usability, workflow and evidence management, role-based access, and performance optimization.

• Familiarity with RMF, CORA, and Department of War cybersecurity assessment and authorization processes.

• Experience supporting commercial or government-off-the-shelf (GOTS) products through government evaluation, accreditation, authorization, or Approved Products List (APL) processes.

• Production experience using Go for endpoint agents, scanners, network services, security tooling, or distributed systems.