Software Engineering Intern

Constellis•Herndon, VA

1d•Onsite

About The Position

Layered Extended Security Operations (LEXSO) is Constellis’ advanced multi-sensor integration platform, purpose-built to deliver real-time situational awareness and operational automation. LEXSO fuses data from distributed sensors, normalizes it into actionable events, and drives automated responses at the speed of sensing across critical infrastructure, military installations, and high-value assets worldwide. Built on a scalable, cloud-native and edge-capable architecture, LEXSO integrates real-time processing pipelines, AI-driven analytics, and secure communications to enable deterministic decision-making in dynamic operational environments.

Requirements

Pursuing a Bachelor’s or Master’s in Computer Science, Information Technology, Cybersecurity, or related field
Experience with modern development and infrastructure tools such as Python, containerization, CI/CD, and distributed systems. Exposure to orchestration, automation frameworks, and data pipelines is a plus.
Familiarity with Git and Linux environments.
Interest in distributed systems and real-time data pipelines.
Desire to learn AWS, Azure, or hybrid edge deployments.
Ability to troubleshoot across system layers (not just code).
Ability to obtain a U.S. Secret Clearance.

Nice To Haves

Exposure to Docker, Kubernetes, or microservices architectures.
Familiarity with CI/CD tools (GitHub Actions, Jenkins, etc.).
Interest in streaming/data systems ( event-driven architectures).
Exposure to monitoring tools (Prometheus, Grafana, ELK stack).
Basic understanding of networking and cybersecurity principles.

Responsibilities

Assist in building and maintaining pipelines that deploy LEXSO services across edge, on-prem, and cloud environments.
Package and deploy microservices using Docker; support container registries.
Contribute to Terraform/Ansible configurations for repeatable deployments.
Support cluster health, scaling, and troubleshooting for real-time workloads.
Help implement logging, monitoring, and alerting for system health, debugging, and auditability.
Support ingestion of raw sensor data (LiDAR, radar, cameras, RF, etc.) into the platform.
Assist in transforming raw data into standardized events (who/what/where/when/how).
Help ensure high-throughput, low-latency processing pipelines for real-time decisioning.
Contribute to embedding location-aware data into events for operational awareness.
Support how processed events trigger automation, alerts, and downstream actions.
Participate in daily stand-ups, sprint planning, backlog grooming, and retrospectives.
Work from Jira epics, stories, and tasks tied to real deliverables.
Contribute to incremental releases supporting live deployments (not theoretical work).
Learn how engineering tradeoffs are made between speed, reliability, and operational execution.
Collaborate across platform, integrations, AI, UI/UX, and field engineering teams.
Work is typically based in a busy office environment and subject to frequent interruptions. Business work hours are Monday-Friday standard core hours, however some extended or weekend hours may be required.