Top Tech Jobs & Startup Jobs

Design, develop, and deploy AI-native software products using multi-agent workflows, large language models, geospatial data pipelines, and cloud infrastructure. Build autonomous agents with tool use, structured reasoning, feedback loops, and reinforcement mechanisms. Develop scalable data ingestion systems, integrate secure enterprise environments, and operate production AI systems using DevOps practices. Contribute to engineering standards and leverage AI-assisted development tools for software design, testing, and documentation.

Develop end-to-end data and machine learning capabilities for Special Operations users. Responsibilities include building scalable pipelines, transforming large datasets, applying advanced analytics and machine learning, deploying models and inference services, developing APIs, and delivering analyst-facing applications. The role requires collaboration with mission users, analysts, engineers, and technical leadership in a customer-site environment.

Leads the enterprise real estate and capital project portfolio, including lease administration, capital planning, budgeting, project governance, and complex project delivery. Develops executive recommendations on cost, risk, timing, and priorities; coordinates with Finance, Legal, Procurement, IT, Security, HR, vendors, landlords, and consultants; manages project managers; and implements portfolio management standards and systems.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Supports AI engineering initiatives at Vantor, contributing to spatial intelligence solutions and helping develop technologies that enable customers to understand current and future conditions. The posting provides limited role-specific responsibilities but emphasizes problem-solving, innovation, collaboration, and mission-focused work. Applicants must qualify as a U.S. Person under applicable export control and ITAR requirements.

Develop and execute employer brand campaigns targeting talent audiences, including technical and security-cleared professionals. Partner with Talent Acquisition, Marketing, employees, leaders, and subject matter experts to create content and coordinate campaigns across career sites, social media, advertising, email, and recruiting events. Analyze audience, channel, and recruiting data, track campaign performance, prepare updates, coordinate vendors, and recommend improvements to content, channel mix, and investment.

Develop and maintain production AI/ML applications centered on agent-based workflows, LLM integration, and RAG pipelines. Build Python REST APIs, integrate external systems and AI frameworks, support full-stack application development, process structured and unstructured data, refine Postgres schemas, and optimize applications for reliability, performance, usability, and scalability. The role requires an active TS/SCI clearance with polygraph and full-time onsite work.

Perform enterprise cyber risk assessments, software scans, third-party risk reviews, access reviews, governance, audit management, and regulatory compliance activities. Develop security standards and procedures, report cyber risk posture and trends, recommend mitigation actions, and engage stakeholders across technical and business teams. The role requires managing risk programs, communicating findings to leadership, and improving security control effectiveness through automation and pragmatic compliance solutions.

Develop and maintain scalable full-stack software for national security applications. Responsibilities include designing features, writing and debugging code, building automated tests, resolving performance bottlenecks, participating in code reviews, collaborating with cross-functional teams and users, and deploying solutions with DevSecOps teams. The role requires JavaScript or TypeScript expertise, front-end framework experience, software development experience, and the ability to work onsite as needed.

Design and deploy production AI systems that transform large-scale geospatial data into actionable intelligence. Build end-to-end ML pipelines, multimodal and reasoning models, experimentation frameworks, synthetic datasets, and scalable inference systems. Collaborate with research, engineering, product, and domain teams while optimizing models for reliability, latency, and cost. Support monitoring, retraining, evaluation, and next-generation Earth AI capabilities.