Technical Lead/Platform Solutions Architect

Technical Lead / Platform Solution Architect

Mission Value: Serve as the technical authority across a complex, multi-vendor AI and software platform, helping the government team make sound architecture decisions, resolve cross-platform integration challenges, and establish repeatable patterns that accelerate mission delivery.

Role Description

Defense Unicorns is seeking a senior Technical Lead / Platform Solution Architect to embed with a government team and serve as the go-to technical subject matter expert across the platform architecture. This individual will connect the mission, engineering, security, data, AI, and vendor perspectives into a coherent technical approach and become a trusted technology advisor to the mission hero.

The role is intentionally hands-on and strategic. The Technical Lead will work across Kubernetes/OpenShift, GitLab and CI/CD, AI/agent infrastructure, enterprise data services, cloud infrastructure, security controls, and integration patterns. They will guide technical decisions, challenge assumptions, identify architectural risks early, and help the team move from prototype to operational capability. The ideal candidate can move fluently between executive-level mission conversations and deep technical discussions with engineers and OEM teams.

Responsibilities

Own the end-to-end technical architecture and serve as the primary technical SME across the platform ecosystem.Become a trusted technology advisor to the mission hero, translating mission objectives into pragmatic technical choices and providing clear recommendations, tradeoffs, and risk assessments.Create and maintain the architectural “big picture” across application, platform, AI, data, networking, security, identity, and integration layers.Lead technical integration across commercial and government technologies, including Kubernetes/OpenShift, GitLab, AI/ML services, enterprise data platforms, and supporting security tooling.Identify architectural dependencies, integration risks, bottlenecks, and technical debt early enough to prevent downstream schedule or mission impacts.Guide engineering teams in establishing repeatable patterns for deployment, configuration, observability, identity, secrets, APIs, data access, and lifecycle management.Work directly with OEM engineering and professional services teams to resolve cross-platform issues and ensure vendor solutions fit the overall architecture.Evaluate emerging AI, agentic, cloud-native, and platform technologies and advise the government team on practical adoption, integration, and sequencing.Help establish technical patterns that can be reproduced across classified environments and support the transition from prototype to operational use.Partner with the DevSecOps engineer to identify security and compliance risks early, incorporating NIST 800-53/RMF and ATO considerations into architecture and engineering decisions.Partner with the Data Engineer and AI Agentic Engineer to ensure data, models, agents, and applications are designed to work together as an operational system.Produce and maintain architecture diagrams, ADRs, technical standards, integration patterns, and concise decision briefs for government leadership.Identify recurring integration and platform problems that can be standardized, automated, or productized through UDS or other reusable capabilities.

Minimum Experience and Qualifications

Active TS/SCI clearance.Local to the National Capital Region and able to support onsite work at a government facility in Springfield, Virginia; availability for increasing onsite/SCIF interaction as the program scales.8+ years of experience in systems engineering, platform engineering, cloud architecture, DevSecOps, or solution architecture, with demonstrated ownership of complex technical environments.Deep hands-on understanding of Kubernetes and enterprise container platforms, preferably Red Hat OpenShift.Strong understanding of cloud infrastructure, CI/CD, Infrastructure as Code, GitOps, APIs, networking, identity, secrets, and observability.Familiarity with NIST 800-53, RMF, ATO/C-ATO, zero-trust architecture, software supply-chain security, and continuous authorization.Ability to understand and communicate system architecture across application, platform, AI, data, and security boundaries.Demonstrated experience leading technical decisions in ambiguous, fast-moving environments with multiple engineering teams and technology vendors.Strong written and verbal communication skills with the ability to brief senior government leaders and collaborate effectively with deeply technical engineers.Ability to serve as a technical point of accountability without becoming a bottleneck; comfortable making informed decisions and escalating when needed.

Preferred Experience and Qualifications

Experience with AI/ML infrastructure, generative AI, agentic systems, model serving, RAG, or AI platform architecture.Experience with Red Hat OpenShift AI, NVIDIA AI technologies, GitLab, enterprise data platforms, or comparable commercial technologies.Experience integrating multi-vendor platforms where no single vendor owns the complete end-to-end solution.Experience supporting Secret or TS/SCI systems and multi-domain or disconnected/air-gapped deployments.Experience with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery and platform engineering technologies.Experience creating architecture decision records, reference architectures, technical roadmaps, and executive-level technical briefings.Experience advising government customers on technology strategy, modernization, platform adoption, or enterprise architecture.

Success in the Role

The government team has a single, trusted technical advisor who can connect mission goals to architecture and engineering execution.Cross-platform integration issues are identified and resolved before they become schedule or mission blockers.Technical patterns become repeatable rather than bespoke, reducing future engineering effort as the environment expands across classifications and mission use cases.The team can make faster, better-informed technology decisions and move from prototype to operational capability with fewer integration surprises.