Top Tech Jobs & Startup Jobs

Designs, develops, deploys, configures, tests, and documents software throughout all phases of the software development life cycle using Java, J2EE, HTML, PL/SQL, T-SQL, and Unix.

Provides executive administrative support to NIH’s National Library of Medicine, including calendar management, meeting coordination, travel planning, procurement, records maintenance, data entry, reporting, and office workflow support. The role manages federal travel and administrative systems, prepares documents and presentations, tracks budgets and personnel actions, ensures regulatory compliance, and coordinates communications, meetings, committees, and special projects.

Leads budgeting, forecasting, revenue and cash-flow analysis, contract profitability, workforce economics, backlog and funding analysis, and management reporting. Provides financial decision support to leadership, automates models and recurring reports, establishes KPI frameworks, and manages and develops the finance team. The role requires onsite work in Tysons, Virginia or Rockville, Maryland.

Leads daily accounting operations, including AP, AR, billing, payroll, general ledger, contract accounting, reconciliations, and month-end close. Manages and develops the accounting team, strengthens internal controls, supports audits, and ensures accurate financial records. Drives automation and process standardization to create scalable operations, resolve discrepancies, maintain audit readiness, and improve billing and reporting workflows.

Provides independent administrative support for NIA/LBN laboratory operations, including travel coordination, correspondence, records, files, equipment, supplies, purchase requests, personnel packages, manuscript editing, and seminar or conference logistics. Serves as a point of contact for lab staff, visitors, and invited speakers; manages office priorities, mail, and administrative procedures. Supports domestic, foreign, sponsored, and local travel arrangements and assists with records management.

Owns the end-to-end infrastructure for a multi-server scientific imaging platform. Responsibilities include Linux administration, Image Artist standardization and upgrades, NVIDIA/CUDA GPU and HPC support, storage and networking troubleshooting, large-scale data migration, security patching, vendor escalation, AI imaging enablement, documentation, and platform health reporting.

Implements and monitors cybersecurity controls across Linux, Kubernetes, database, and model-serving environments. Builds monitoring, detection, vulnerability scanning, hardening automation, secrets management, network policy, access control, and evidence collection. Supports AI security tooling, documentation, testing, security reviews, continuous monitoring reports, and federal authorization activities. This early-career role includes hands-on training, certification support, and collaboration with AI and systems administration leads.

Leads hybrid cloud and on-premises IT operations across Linux and Windows environments. Responsibilities include ITIL-based incident, problem, change, and release management; systems hardening, patching, vulnerability remediation, automation, monitoring, and observability. The role supports AI/ML and GPU-enabled workloads, manages operational readiness and documentation, and mentors systems engineers while driving reliability, scalability, and infrastructure improvements.

Build production AI retrieval and knowledge systems for rare disease research at NIH. Model biomedical ontologies in PostgreSQL, develop semantic search, retrieval-augmented services, ranking, evaluation, and observability, and deliver user interfaces with Next.js, React, and TypeScript. Deploy and operate services in on-premises and HPC Kubernetes environments, including GPU inference. Collaborate with NIH staff, clinicians, and researchers, and contribute to scientific publications.

Build and operate agentic AI systems for rare disease research, including multi-turn workflows, structured and validated outputs, tool calling, prompt testing, evaluation suites, asynchronous execution, streaming, observability, and failure handling. Collaborate with NIH staff, clinicians, geneticists, researchers, and patient communities to translate needs into reliable data models and system behavior. Own components through deployment, establish AI engineering standards, and contribute to scientific manuscripts, abstracts, and conference posters.