Senior AI Software Engineer & Developer

NOTE: This opportunity is full-time employment position only (no 1099 or C2C engagements, or third parties or staffing agencies, please). The candidate MUST be a U.S. Citizen and Permanent Resident (Green Card holder). This is a remote opportunity; candidate must be based in the U.S.; have resided in the U.S. for at least 3 years in the past 5 years; ET time zone work schedule.

Daily Responsibilities

• Serve as a senior, hands-on full-stack AI engineer and technical authority, leading the technical strategy, design, and delivery of large-scale mission-critical AI systems supporting federal programs.
• Serve as the primary technical authority, defining AI and application architecture across multiple programs.
• Establish enterprise modernization roadmaps aligned to mission outcomes, compliance, and scalability.
• Lead architecture for distributed, cloud-native, and hybrid AI systems.
• Define and enforce reference architectures, standards, and reusable frameworks.
• Drive cross-program technical decision-making to ensure interoperability, security, and long-term sustainability.
• Advise senior federal stakeholders (SES-level and above) on AI adoption, modernization, and risk management.
• Lead design, development, and deployment of advanced AI solutions using Python as the primary development language, including large language models (LLMs) and foundation models, Retrieval-Augmented Generation (RAG) systems, agentic workflows, and orchestration frameworks.
• Architect and implement scalable ML systems and services built on Python-based frameworks and APIs.
• Build full-stack AI applications end to end, from user-facing interfaces to back-end services, APIs, and data layers.
• Integrate AI and LLM capabilities into existing enterprise applications and legacy platforms (e.g., content management, case management, and records systems) via APIs, middleware, and event-driven patterns.
• Define and implement distributed training strategies (GPU/TPU clusters, parallelization, optimization).
• Oversee full ML lifecycle in partnership with the senior data scientist: data pipelines, feature engineering, training, evaluation, deployment, and monitoring.
• Drive model optimization techniques (quantization, distillation, caching) to improve performance and cost.
• Establish robust MLOps practices leveraging Python-driven automation, pipelines, and tooling.
• Stand up the enterprise CI/CD-to-AI/MLOps pipeline, beginning with time-boxed proofs of concept and MVP implementations that mature into production systems.
• Serve as SME in federal AI policy (e.g., NIST AI RMF, OMB M-25-21 and M-25-22, Executive Order 14179).
• Define and operationalize Responsible AI frameworks, including model validation and evaluation, bias mitigation and fairness, and explainability, auditability, and safety.
• Ensure compliance with FISMA, FedRAMP, NIST 800-53, privacy, and Section 508 requirements.
• Lead large-scale modernization initiatives (e.g., legacy-to-cloud, microservices transformation, including Python-based refactoring and re-platforming efforts).
• Define repeatable modernization frameworks and accelerators.
• Oversee DevSecOps pipelines, CI/CD automation, zero-trust architectures, and secure software supply chain practices.
• Ensure delivery of resilient, high-availability systems in regulated federal environments.
• Lead multiple concurrent engineering efforts across integrated teams.
• Provide technical leadership to architects, engineers, and DevSecOps specialists, including establishing Python coding standards and engineering best practices.
• Mentor senior engineers and technical leaders; elevate engineering excellence and code quality.
• Support technical strategy in proposals, captures, and client engagements.
• Contribute to thought leadership (whitepapers, architecture patterns, platform strategy).
• Executive communication skills with experience influencing senior leaders.