Senior Software Engineer - Core

Cavnue

2d•Remote

About The Position

Cavnue, a Consor company, is redefining what's possible for modern transportation infrastructure. As the digital infrastructure platform within Consor Engineers, a leading North American engineering and advisory firm, Cavnue combines advanced roadway technology with deep transportation design and delivery expertise to modernize how roads are operated and managed. We believe the future of roadways is connected, intelligent, and designed to actively improve safety, efficiency, and accessibility for all users. While vehicle technologies such as advanced driver assistance systems and automated driving continue to evolve rapidly, roadway infrastructure must evolve alongside them. Cavnue is closing that gap by developing and deploying smart road technologies that deliver a real-time digital twin of the roadway environment, leveraging AI-enabled analytics, sensors, cameras, and integrated digital infrastructure to provide actionable operational insights. Together with Consor, we are accelerating the deployment of these solutions at scale, helping public and private clients modernize infrastructure and prepare for the next generation of mobility. With active projects across the United States, our work is setting a new standard for roadway performance today while laying the foundation for a safer, more efficient, and more connected transportation future. Join us as we shape the future of infrastructure where digital innovation meets engineering excellence to deliver measurable real-world impact. Role Overview We are looking for a Senior Software Engineer who is equally comfortable writing high-performance C++ as they are shipping Python services, and who can reason clearly about algorithms, data structures, and system behavior under load. This is a broad, hands-on role working across the full depth of our platform, including building data replay infrastructure for system validation, aggregating traffic data over spatial and temporal windows to generate real-time insights and incident records, improving object tracking algorithms, and ensuring video and sensor data flows reliably from edge devices to the cloud, routing data to AI models for verification and classification. You will focus on making these systems observable, performant, and production-ready. Our architecture centers on strong API interfaces, supported by a robust stack including PostgreSQL for persistence and Terraform, Helm, and Argo for infrastructure and deployment. You will collaborate across engineering teams to integrate new product features into efficient, low-latency services, while leveraging Datadog to ensure deep visibility into system health. This is a fully remote, hands-on individual contributor role with meaningful ownership across core systems. We are looking for a generalist who can operate autonomously end to end, from design through deployment and ongoing operation, while using AI-assisted tools thoughtfully to move faster without compromising quality. You think beyond the code, connect your work to the broader product and user experience, and take initiative to turn ideas into action in ambiguous environments.

Requirements

5+ years of professional software engineering experience with a strong backend and systems focus.
Proficiency in Python and C++ in production environments, with the ability to choose the right tool for the job and ship quality code.
Strong fundamentals in algorithms, data structures, and systems design; able to reason about computational complexity and system behavior under constraints.
Experience building and operating real-time or streaming data systems (e.g., Redis Streams, Kafka, Pulsar, Flink).
Experience with scientific/numerical Python libraries (NumPy, SciPy, Pandas), GCP (or comparable cloud infrastructure), containerization (Docker/Kubernetes), and Infrastructure as Code/CI/CD pipelines (Terraform, GitHub Actions, GitLab CI, etc.).
Comfortable working in Linux and with agentic coding tools (e.g., Claude Code, Cursor, or similar AI-assisted environments).
You are a generalist who can ramp up quickly on unfamiliar domains, codebases, and technologies, keeping the product and users in mind.
Self-starter who spots gaps, proposes solutions, makes decisions with imperfect information, and drives work forward independently.
Strong communication skills to explain architectural decisions clearly to both technical and non-technical stakeholders.
BS in Computer Science, Engineering, or equivalent practical experience.

Nice To Haves

Domain experience in transportation, robotics, autonomous vehicles, or sensor-heavy systems.
Familiarity with classical estimation and filtering techniques, including Kalman filters, Bayesian methods, and sensor fusion, sufficient to read, integrate, and debug implementations.
Experience with GCP data products (BigQuery, Cloud Storage, Pub/Sub) and AI/ML workflows, feature stores, or model serving infrastructure.
Familiarity with messaging and observability tools such as nanomsg and OpenTelemetry.
Experience with high-throughput data processing techniques and integrated build systems like Buck2.
Prior experience in early-stage startup environments.

Responsibilities

Build and maintain high-throughput, low-latency Python and C++ services, owning the full lifecycle from development to monitoring and incident response.
Design and optimize data structures, Protobuf serialization, and Redis Streams for real-time data processing workloads.
Architect and manage data pipelines from raw sensor ingestion to transformation, storage, and delivery.
Integrate low level, tracking, inference and sensor fusion algorithms into production services.
Develop REST APIs and internal/external service integrations.
Implement observability, CI/CD pipelines, and infrastructure as code (Terraform) for reliable, repeatable deployments.
Operate containerized services on Kubernetes (using Argo and Helm) in GCP; document systems, runbooks, and integrations.
Contribute to a healthy, high-trust engineering culture where good ideas can come from anywhere.