Forward Deployed Engineer (FDE) C-UAS

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

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.

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.

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.

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.

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

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

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

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 Clearance: Active TS/SCI required. Travel: Approximately 10%–25%, based on mission and customer requirements.

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 code (Terraform, Pulumi, or similar) and GitOps deployment practices. A