Top Tech Jobs & Startup Jobs

Lead DevSecOps work to design, provision, and secure production Kubernetes/Docker clusters and CI/CD/GitOps pipelines for a real-time, data-intensive DoD platform. Deploy and operate streaming systems (Kafka/Pinot/Flink), implement IaC, monitoring, and logging, and ensure compliance and security (active Top Secret required).

Own full-cycle recruiting for technical and corporate roles, manage candidate journey from intake to offer, source and close cleared technical talent, partner with hiring managers on clearance/citizenship requirements, maintain ATS and sourcing tools, build diverse pipelines, and manage a high-volume requisition load.

The role involves building data-focused products using various technologies, focusing on backend and frontend development, RESTful APIs, and cloud-native solutions, while ensuring data accessibility through innovative design and architecture.

The Program/Product Manager will oversee program health, manage Agile software development teams, engage with DoD stakeholders, and ensure program success while adapting to evolving requirements.

The Lead AI/ML Engineer will oversee the design, development, and deployment of AI solutions, manage cross-functional teams, and ensure system reliability and performance in mission-critical environments.

The Senior Sales Engineer will bridge product and sales teams, translating technical capabilities into compelling narratives, leading demos, and managing customer engagements to drive business growth in defense technology.

Design, harden, and operate secure Kubernetes-based platforms across cloud, on-prem, disconnected, and classified environments. Own GitOps/CI/CD, IaC, supply-chain security, observability, compliance automation, and MLOps support. Mentor engineers, troubleshoot distributed systems, and engage with customers to ensure deployable, compliant, and observable mission systems.

Design, build, and operate large-scale, fault-tolerant streaming data platforms and ETL pipelines using Kafka, Flink/Pinot and cloud-native tooling. Deploy and troubleshoot containerized applications on Kubernetes, ensure low-latency data storage/retrieval, and apply software architecture best practices for mission-critical government systems.

Lead technical design and execution for an AI/ML mission platform: drive architecture decisions, lead major engineering epics, simplify distributed systems, optimize edge and cloud performance, mentor engineers, integrate ML models and inference pipelines, and represent technical capabilities to DoD stakeholders.

The AI/ML Engineer will develop and evaluate machine learning models, integrate them into the [R]AIMS platform, and ensure operational deployment. Collaboration with engineers and mission stakeholders is essential.