Senior Integration Engineer - Platform / Agentic AI

We believe the future of our nation’s roadways is automated, safer, more accessible and enables more efficient movement of people and goods. While billions have been invested into developing vehicle technologies – including advanced driver assistance systems (“ADAS”) and autonomous driving solutions – a small fraction has been spent on developing infrastructure to support and enhance roadways. At Cavnue, we are developing and integrating technologies that will power the world’s most technologically advanced roadways (“cavnues”). Our approach is founded in creating a digital model of the roadway that analyzes and optimizes road conditions in real-time, sharing actionable alerts and providing proactive guidance to vehicles and drivers.

Join us in innovating the roads of the future. Cavnue, which in April 2022 announced the closing of its Series A at $130M, is bridging vehicle technology and road infrastructure to rapidly deliver safer roads today while accelerating the adoption of connected and automated vehicles (CAVs) moving forward. With ongoing deployments in Michigan and Texas, Cavnue is the only company in North America that uses Smart Road technology to improve performance for road operators and deliver a safer, more efficient experience for all road users while preparing for a future with more CAVs. Our mission is to set the new standard for road performance and safety.

Role Overview

We seek an experienced Platform/Integration Engineer with a strong foundation in systems engineering. You will be responsible for designing, building, and maintaining robust services and integration solutions that incorporate real-time data processing and state estimation from various sensor inputs. This fully remote role involves collaborating with cross-functional teams to develop and deploy systems where accurate estimation and prediction based on classical methods are critical. Join us to build the foundational systems that power intelligent applications through sophisticated data interpretation.

Core Responsibilities:

• Expert with Python and using technologies such as Postgres.
• Drive production of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve.
• Engineer data structures, databases, and data lakes for optimal performance and reactivity in a production environment.
• Develop and maintain APIs, and integration patterns to support the deployment, orchestration, and operation of AI agents and multi-agent systems. This role focuses on building the "Platforms for AI" rather than using AI within the platform itself. Take the AI into production.
• Implement comprehensive monitoring, logging, and alerting for platform health, data quality, and algorithm performance.
• Collaborate closely with hardware engineers, software developers, and researchers on sensor selection, system architecture, calibration procedures, and resolving integration challenges.
• Maintain clear documentation for algorithms, system designs, integration points, and operational procedures.
• Assurance of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve
• Establish low-latency/high throughput APIs on streaming packets of data from the cloud and edge
• Contribute to a health and positive engineering culture

Nice to Have Responsibilities:

• Work in a number of languages (Python, C++, Go), established libraries and technologies (Redis, BigQuery, Pulsar, Flink) and development environments (K8s, NVIDIA Jetson)  
• Experience with technologies like Apache Spark or Kafka
• Design, build, manage, and optimize scalable, secure, and cost-effective infrastructure and platforms specifically tailored for AI/ML workloads on cloud platforms
• Support the frameworks that enable fine-tuning, serving, and monitoring Large Language Models (LLMs) efficiently and reliably.
• Build and manage scalable data ingestion, storage (e.g., data lakes), and processing pipelines optimized for ML training data and feature engineering.
• Stay current with the latest advancements and best practices in AI/ML, MLOps, LLMs, and agent technologies, driving continuous improvement. The rapid evolution of this field necessitates constant learning and adaptation.

Requirements:

• 5+ years of professional experience in software engineering, platform engineering, or integration engineering.
• Bachelors Degree in Computer Science, Engineering or equivalent experience
• Proficiency in programming languages commonly used for both platform development and algorithm implementation, such as Python and C++
• Experience with cloud platforms (AWS, Azure, or GCP) and core infrastructure servic