Principal AI Software Developer
Overview
The Senior Principal Software Engineer/Developer will serve as a lead enterprise architect and AI engineering authority, responsible for defining and delivering large-scale, mission-critical AI-enabled systems for HUD and the AIR platform. This role goes beyond hands-on development to include enterprise-wide technical strategy, cross-program architecture leadership, executive-level stakeholder engagement, and AI governance and innovation leadership in federal environments.
Responsibilities
- Serve as the primary technical authority across multiple programs, defining AI and application architecture strategy at the enterprise level
- Establish long-term modernization roadmaps for federal systems, aligning AI adoption with mission outcomes and compliance requirements
- Act as a trusted advisor to senior federal stakeholders (SES-level and above) on AI strategy, system modernization, and technology risk
- Drive technical decision-making across portfolios, ensuring scalability, interoperability, and long-term sustainability
- Own end-to-end enterprise architecture across multiple interconnected systems, platforms, and programs
- Lead design of complex, distributed AI-enabled architectures, including multi-cloud and hybrid environments
- Define and enforce architecture standards, reference architectures, and reusable frameworks across teams
- Lead development of advanced AI solutions, including RAG systems at scale, agentic workflows and orchestration frameworks, and AI-driven automation across mission workflows
- Establish AI engineering best practices and standards across the organization
- Evaluate and lead adoption of emerging AI technologies, guiding pilots into production-ready capabilities
- Drive innovation initiatives tied to AIR platform growth and differentiation
- Oversee multiple concurrent development efforts, ensuring alignment with architecture, security, and delivery goals
- Provide technical leadership across integrated product teams, including architects, engineers, and DevSecOps specialists
- Ensure delivery of high-availability, production-grade systems supporting federal missions
- Serve as a subject matter expert in federal AI policy and governance, including NIST AI RMF, OMB M-24-10, and EO 14110
- Establish and oversee organization-wide responsible AI frameworks, including model evaluation and validation, bias mitigation strategies, and explainability and auditability
- Ensure full compliance across programs with FISMA, FedRAMP, NIST 800-53, privacy, accessibility (Section 508), and security mandates
- Lead large-scale legacy modernization initiatives, including enterprise COBOL-to-Python transformations, migration to cloud-native, and microservices-based architectures
- Define repeatable modernization frameworks and accelerators
- Oversee implementation of enterprise-grade DevSecOps pipelines and platform engineering practices
- Drive adoption of, advanced CI/CD automation, Zero-trust architectures, and secure supply chain practices (SBOM, scanning, policy enforcement)
- Mentor senior engineers, architects, and technical leads
- Build and scale high-performing engineering teams
- Lead technical hiring, workforce planning, and capability development
- Play a key leadership role in proposals, captures, and recompetes
- Serve as technical lead in client presentations, demos, and strategy sessions
- Contribute to thought leadership (whitepapers, architecture frameworks, innovation roadmaps)
Qualifications
Knowledge/Skills/Abilities: Initial:
- Proven ability to operate as an Enterprise architect, chief engineer, or technical director-level leader
- Strong executive communication skills with demonstrated success influencing C-suite or federal senior leadership
- Deep expertise in scaling engineering organizations and delivering across complex programs
- Ability to balance strategic vision with hands-on technical depth
Qualifications:
- US Citizenship is required
- Bachelor's or master's degree in Computer Science, Software Engineering, or a related field
- 12–15+ years of software engineering experience, including 6–8+ years in AI-enabled systems (LLMs, generative AI, applied ML in production) (enhanced from 8+ years total)
- Demonstrated experience leading enterprise-scale architecture and multi-team delivery efforts
- Expert-level proficiency in Python and modern backend frameworks and Full-stack architectures and modern front-end technologies
- Deep experience in Cloud-native platforms (Azure, AWS, GCP) at scale and Multi-environment deployments in FedRAMP-authorized environments
- Extensive experience with AI/ML platforms (OpenAI, Bedrock, Vertex AI, etc.) and Advanced AI architectures (RAG, orchestration, agents)
- Proven track record of leading large modernization programs (COBOL-to-modern stack transformation) and delivering mission-critical federal systems
- Deep knowledge of NIST AI RMF and federal AI governance frameworks and secure software development in federal environments
- Strong experience with Microservices, APIs, distributed systems design and DevSecOps and platform engineering leadership
- Prior experience serving as Lead Architect, Chief Engineer, or Technical Director on federal programs
- Active clearance (Public Trust, Secret, or higher strongly preferred)
- Prior HUD or federal civilian agency leadership experience
- Experience contributing to organizational AI strategy or product platforms (e.g., AIR-like platforms)