Senior Python Developer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Python Developer based in the United States. 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. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 Accountabilities Design, develop, test, and optimize Python-based scanning capabilities that perform reliably across large, segmented, and federated network environments, including restricted government settings. Build and integrate production AI capabilities using local, self-hosted models and cloud-hosted AI services, selecting appropriate architectures based on security, connectivity, accuracy, performance, and cost. Develop AI-assisted workflows for ingesting, interpreting, structuring, and validating new and updated DISA Security Technical Implementation Guides (STIGs), including the management of organizationally defined parameters and cybersecurity content mappings. Automate complex cybersecurity and product workflows through intelligent document processing, structured data extraction, classification, transformation, validation, exception handling, and human-in-the-loop review. Establish measurable outcomes for AI-driven automation, including accuracy, throughput, quality, and processing time. Integrate and orchestrate AI models through maintainable abstractions that support different mission environments and technical requirements. Contribute to the AI/ML lifecycle, including dataset preparation, model selection, evaluation, prompt engineering, retrieval design, fine-tuning and other adaptation techniques, inference optimization, validation, and production monitoring. Expand cybersecurity compliance coverage beyond operating systems to include applications, databases, application servers, middleware, and other software layers. Own development initiatives from planning through deployment and stabilization, resolving customer findings and communicating progress, risks, dependencies, and technical trade-offs to product leadership. Maintain high engineering standards through architecture contributions, code reviews, automated testing, documentation, observability, secure development practices, and production support. Provide technical leadership by exercising independent judgment, influencing architecture and prioritization decisions, mentoring developers, and improving engineering practices. Collaborate with architecture, dashboard, cybersecurity content, product, and customer-facing teams to align scanner outputs, AI-generated and ingested content, validation workflows, and reporting. Requirements 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. Benefits Employment type: Full-time. Work arrangement: Fully remote within the United States. Paid time off: Paid holidays and paid time off. Retirement savings: 401(k) plan with employer matching. Healthcare: Health insurance plans. Dental and vision: Dental and vision coverage. Additional insurance: Life and disability benefits. Technical challenge and ownership: Opportunity to work on production AI, cybersecurity automation, and software supporting complex federal and defense environments.