Software Engineer, Cloud Engineer - Software

Route Smart Technologies
, a leader in vehicle route optimization software technology, is seeking a Software Engineer to join our development team. This role will report directly to the Manager, Software Engineering and is responsible for designing, developing, and supporting modern, scalable applications and services as part of a next‑generation platform initiative.

This position will play a key role in building a new generation of software that redefines how we design, develop, and deliver products. Unlike incremental upgrades, this initiative focuses on creating something entirely new using a Spec‑Driven Development (SDD) approach powered by Large Language Models (LLMs). The role involves contributing to AI‑assisted engineering workflows, building cloud‑native systems, and helping shape the future of software development at Route Smart.

The Software Engineer will work in an exploratory, fast‑evolving environment where not all requirements are fully defined. Success in this role requires curiosity, adaptability, and a willingness to experiment with new tools, frameworks, and methodologies. Responsibilities include developing high‑quality code, collaborating across teams, and contributing to the definition of new engineering standards. Experience with cloud‑native technologies (Linux, Docker, Terraform) and modern development practices is highly valued.

The ideal candidate is passionate about innovation and thrives in solving complex, ambiguous problems. They will contribute to delivering reliable, high‑quality solutions while helping drive forward Route Smart's next generation of technology. Strong technical skills, attention to detail, and the ability to collaborate effectively within a dynamic team environment are essential.

The typical base pay range for this position at the start of employment is expected to be between $95,000-$145,000 per year. Route Smart Technologies, Inc. has different base pay ranges for different work locations within the U.S., and base pay will vary based on experience.

This is a hybrid role; candidates must be able to commute to the office in Melville, NY or Columbia, MD. Candidates must reside within 50 miles and be available to work onsite several days per week. However, we will consider the right candidate for remote work if domiciled in one of the following states:
Maryland, New York, Pennsylvania, Arizona, California, Colorado, Florida, Idaho, Illinois, Indiana, Minnesota, New Jersey, North Carolina, Oregon, South Carolina, Washington.

• Orchestrate AI across the SDLC by utilizing LLM co‑pilots during design, coding, testing, debugging, and optimization
• Convert product requirements into structured specifications that drive deterministic system behavior
• Partner with AI tools to generate APIs, services, and workflows directly from written specifications
• Refine prompts and development workflows to ensure consistent, high‑quality, and secure code outputs
• Design clean, modular, and composable microservice architectures using best‑fit technologies
• Use AI to rapidly understand, extend, and refactor systems across diverse technology stacks, including:
• Rust / Go for performance‑critical backend services
• Python / Node.js for orchestration and rapid iteration
• Java / .NET for enterprise‑grade workloads
• React / Angular (Type Script) for web applications
• Swift / Kotlin for mobile applications
• Integrate AI capabilities into systems for real‑time decisioning, automation, and unstructured data processing
• Design and operate resilient, cloud‑agnostic infrastructure (initially AWS) using Docker and Terraform
• Build and manage modern CI/CD pipelines to enable safe and frequent delivery
• Ensure systems are secure, observable, scalable, and cost‑efficient
• Review and validate AI‑generated code to prevent security vulnerabilities (OWASP Top 10) and performance issues
• Integrate automated, AI‑driven validation checks into build and deployment pipelines
• Perform ongoing threat modeling across distributed, multi‑language systems
• Serve as the final human validator for AI‑driven architectural and logical decisions
• Identify and mitigate risks such as model bias, hallucinations, or…