Lead Network Software Engineer

Leidos•Huntsville, AL

1d•$107,900 - $195,050•Onsite

About The Position

Leidos has a new and exciting opportunity for a Lead Network Software Engineer in our National Security Sector's (NSS) Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. The Lead will support DARPA QuANET and the position builds on building and testing software that integrates network emulation, routing, telemetry, and cyber‑response logic. The developer will work hands‑on with Python and C++, create reproducible test environments, debug Linux and container networking issues, and collaborate with senior engineers across hardware, cyber, and networking teams. Strong systems and distributed‑networking skills are essential; quantum‑domain experience is not required. Candidates with deep implementation ability and broad networking expertise are preferred.

Requirements

Bachelor's degree in computer science, computer engineering, electrical engineering, networking, or a related technical field, and 8+ years of relevant experience; additional relevant experience may be considered in lieu of degree.
Experience leading the design and execution of routing, network emulation, telemetry, and network-response capabilities.
Deep routing protocol knowledge, including protocol-internals understanding of BGP, OSPF, IS-IS, or comparable protocols.
Experience with SPF behavior, LSA flooding, path attributes, convergence behavior, and routing tradeoffs.
Hands-on Linux networking experience, including namespaces, veth pairs, iproute2, iptables/nftables, and tc.
Docker or container networking experience, including bridge, macvlan, host modes, CNI plugins, and nested networking failure modes.
Experience with open-source routing stacks such as FRR, Bird, Quagga, or similar.
Hands-on programming experience in Python and C++, with ability to read, write, and review production-quality code.
Experience with network simulation or emulation at scale.
Experience implementing CI/CD, regression testing, or reproducible validation pipelines for networking or systems projects.
Experience with distributed systems, network telemetry, or state-distribution mechanisms.
Ability to lead technical work under ambiguity while remaining hands-on with implementation and lab execution.
Must be a US citizen with ability to obtain and maintain a US government security clearance.

Nice To Haves

Experience with gNMI, OpenConfig, streaming telemetry, or comparable observability/control-plane data sources.
Open-source routing or network-stack contribution history.
Prior experience on government-funded R&D programs such as DARPA, IARPA, ONR, AFRL, ARL, DOE, or NSF.
Experience leading small technical teams in high-ambiguity research, prototype, or advanced development environments.
Experience presenting and defending technical approaches to government customers, technical reviewers, or external advisors.

Responsibilities

Lead the design and execution of routing, network emulation, telemetry, and network-response capabilities for the program.
Translate open-ended R&D objectives into concrete technical plans, experiments, software tasks, and integration milestones.
Own container-to-routing-protocol integration in the team's network emulation environment.
Guide implementation in Python and C++, including design review, pull request review, and technical debugging.
Build and maintain scalable network simulation or emulation environments for large virtual topologies.
Integrate distributed telemetry and cross-component state data into routing and network response decisions.
Establish reproducible CI/CD, regression testing, and experiment validation workflows for network code.
Coordinate standing technical co-design with adjacent teams so interfaces, assumptions, and dependencies remain explicit.
Represent technical decisions in customer, PI, advisor, and program-management discussions with evidence-based reasoning.
Communicate technical risks, tradeoffs, and status clearly to both technical and non-technical audiences.