Forward Deployed Engineer (FDE) C-UAS

Defense Unicorns · Remote

  • Junior
  • Full-time
  • $148,750 – $201,250
  • Posted 2026-11-05
  • Confirmed live on 10 November 2026

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Job description

EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION REQUIRES U.S. CITIZENSHIP.

Role Description

This is a forward-deployed engineering role. You'll work shoulder-to-shoulder with mission heroes- the users, operators, and program engineers who run real workloads in real DoD environments- and lead the software integration of modular Counter-Unmanned Aerial Systems (C-UAS) sensors and effectors. You will deploy, harden, integrate, and operate our modular C-UAS solution.

Forward-deployed means aligned with the mission hero, not always on a plane. Most of the work is remote. You'll travel to sites when the engagement genuinely calls for it — initial standup, in-SCIF integration work, on-the-ground incident response, training, and knowledge transfer- and you'll be on a video call or in a shared chat with that same mission hero the rest of the time. The job is being their engineer, not living at their desk.

You are a cross-functional engineering leader. You can take responsibility for the full breadth of a data and software integration platform- make it work where it has to work, analyze what's running through it, and solve problems in real time for the mission hero. About 20% of your time, you'll also help make Defense Unicorns' forward-deployed team better — pairing with junior Data Engineer FDEs on hard problems, helping them develop technical judgment, and raising the ceiling on what the team can take on.

Responsibilities

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Deploy and harden UDS Data Capability in the mission hero's environment — stand up UDS Store (Iceberg, Rook/Ceph, pgvector, Postgres), wire up UDS Transit for air-gap data movement, configure UDS Govern policies (Pepr/Lula), and integrate UDS Connect (Strimzi/Kafka) where streaming or legacy connectors are required.

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Own integration with existing mission systems — connect UDS Data Capability to existing infrastructure, including sensor arrays, computer-vision-enabled UAS interceptors, and a broad range of C-UAS solutions.

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Build pipelines that move data through classification boundaries — ingestion, transformation, catalog registration, model/dataset packaging via Zarf, cross-domain transit, and eventual consistency across DDIL conditions.

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Operate what you deploy — own initial day-2 operations, including capacity, performance, backup/restore (Velero), observability (Vector/Loki), incident response, and upgrade paths. Transition ownership to the mission hero's operations team once stable.

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Generate accreditation artifacts — STIG evidence, cATO documentation, FIPS validation notes, and policy mappings to support ISSM/ISSO requirements in IL4/IL5 environments.

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Represent the mission hero to product and engineering — document issues, write postmortems, recommend operator improvements, and communicate field challenges to the platform engineering team.

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Train and transfer knowledge — develop runbooks, architecture documentation, working sessions, and knowledge-transfer materials that enable mission teams to operate independently.

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Mentor junior Data Engineer FDEs — pair on complex problems, review integration designs, and help engineers develop technical judgment without direct people-management responsibilities.

Clearance & Travel

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Clearance: Active TS/SCI required.

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Travel: Approximately 10%–25%, based on mission and customer requirements.

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On-site expectations: Ability to work in SCIFs and other restricted environments for days or weeks when required for integration, incident response, training, or knowledge transfer. Most work is performed remotely.

Required Qualifications

• Experience working in tactical edge and interoperable mission environments, including TAK Server administration, ATAK/WinTAK, tactical communications, and disconnected or air-gapped systems.

• Production experience with modern data platforms, including lakehouse technologies (Apache Iceberg, Delta Lake, or Hudi), object storage (Ceph or S3-compatible), PostgreSQL, and analytical query engines such as Trino, DuckDB, ClickHouse, or Spark SQL.

• Experience with streaming and data integration technologies, including Kafka or equivalent messaging platforms, stream processing, change data capture (CDC), and integration of legacy systems into modern data pipelines.

• Hands-on experience building, scheduling, monitoring, troubleshooting, and recovering production data pipelines using Airflow, Dagster, Argo Workflows, or comparable orchestration tools.

• Working knowledge of data governance, cataloging, access control, and auditability, including REST catalogs, ABAC/RBAC, OIDC/OAuth, and data lineage.

• Strong SQL proficiency and experience designing data models and schemas for analytical and operational workloads.

• Hands-on production Kubernetes experience, including deployments, operators, CRDs, storage classes, networking, and troubleshooting.

• Strong Linux, containerization, networking, TLS, and secrets-management fundamentals.

• Experience with infrastructure as c

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