Distributed Command & Control (DC2) Systems Research Engineer / Computer Scientist

Job Overview

OPEN TO ALL QUALIFIED US CITIZENS.

This announcement will be accepting candidate submissions until 11:45 PM EST, 30 November 2026.

The Information and Spectrum Warfare Directorate (RF), Information Systems Division (RFC) is seeking a mid-level, DR-02 (GS-12/13 or equivalent), Distributed Command and Control (DC2) Computer Scientist, Computer Engineer, or Electronics Engineer in Rome, New York.

The incumbent will serve as a core technical systems engineer and software researcher, assisting the senior Distributed C2 team in advancing resilient, decentralized Battle Management Command and Control (BMC2) capabilities for contested operational environments. The scientist/engineer will bridge theoretical architectures and hands-on experimental deployment, solving critical survivability challenges in Denied, Degraded, Intermittent, and Limited-bandwidth (DDIL) operational environments.

Position Duties Include, But Are Not Limited To

• Resilient Data & Database Architecture: Research, prototype, and benchmark robust bidirectional database synchronization and replication mechanisms bridging cloud-based repositories and tactically deployed on-premises nodes under severe DDIL network constraints.
• BMC2 Software Modernization & Microservices: Refactor legacy BMC2 algorithms (e.g., dynamic routing and mission planning logic) into secure, highly decoupled microservices using modern languages (Go, Rust, C++, Java). Containerize services for orchestration across hybrid cloud-to-edge networks (Docker, Kubernetes) and integrate localized, air-gapped Large Language Model (LLM) pipelines, utilizing vector search and Retrieval-Augmented Generation (RAG), to process complex operational tasking data in disconnected environments.
• Distributed Battle Lab & Simulation Testbeds: Integrate, operate, and expand in-house battle lab simulation test beds, ingesting operational data feeds to stage realistic multi-echelon scenarios and validate experimental distributed C2 software to support major exercise de-risking.
• Agentic AI & Kill Chain Decision Support: Collaborate with senior researchers to design, implement, and evaluate multi-agent orchestration frameworks and algorithmic decision-support tools that automate dynamic weapon-target pairing and Long Range Kill Chain (LRKC) plan synthesis.
• Operational Experimentation & Transition Support: Participates in high-visibility joint field experiments and exercises monitoring live data replication telemetry, diagnosing real-time system/network anomalies, and transitioning proven technologies into baseline Air Force programs of record.

Required Qualifications

• US Citizenship.
• Ability to obtain/maintain a Top Secret clearance as a condition of employment.
• Males must be registered for Selective Service, see www.sss.gov.
• This is a drug testing designated position. The incumbent will be subject to random testing.
• Applicants must be able to meet the OPM Qualification Standards of the position being filled: possess a professional Science or Engineering (S&E) degree, in a relevant technical field, from an ABET accredited academic institution.
• This is an Acquisition Professional Development Program (APDP) position requiring Level/Tier 1 (Intermediate) certification in the Engineering & Technical Management stall. Applicants must list all completed APDP certifications on their resume. Selectee will have 5 years to meet the APDP certification requirements of the position.

Desired Qualifications

• Master of Science (M.S.) or PhD in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, or a closely related STEM discipline.
• Hands-on experience with active-active database replication, data-mesh architectures, distributed consensus mechanisms, or data synchronization across disadvantaged, high-latency, or packet-loss networks (DDIL).
• Working knowledge of Air Force Command and Control (C2) operations, Air Operations Center (AOC) systems, or operational planning formats (e.g., USMTF, Air Tasking Orders [ATOs], or C2Core).
• Familiarity with applied AI/ML architectures, including vector databases, language model integration, or multi-agent frameworks for automated planning.
• Experience configuring and operating combat simulation environments, Distributed Interactive Simulation (DIS) protocols, or synthetic testbeds (e.g., MACE, RedSim, AFSIM).
• Demonstrated ability to collaborate and communicate effectively within multidisciplinary teams comprising civilian scientists, active-duty military operators, academia, and defense contractors.

Telework

Yes, this position is eligible for situational telework; as determined by agency policy

Eligible for a Referral Bonus?

No

Series

0854

0855

1550

Additional Information

Instructions on how to submit documents are provided in the automated email you will receive once you apply. Candidates with resumes longer than 2-pages will not be considered.

To ensure your resume meets all federal standards, follow the official guidelines provided by the USAJobs Help Center at the following link: https://usajobshelp.opm.gov/hc/en-us/articles/52839989720851-How-do-I-write-a-resume-for-a-federal-job

Requisition Number 05413

Posting End Date

11/30/2026