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# AI Backend Systems Engineer

- **Company:** Blue Signal
- **Location:** Mount Pleasant Township, PA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Logic, Systems Engineering, Cloud Computing, Databases, Data Stores, Relational Databases, Distributed Systems, Python (Programming Language), Language Modeling, Node.Js, Open Source Technology, OpenAI, Systems Integration, Workflow Management Systems, Pytorch, Large Language Models, Reliability of Systems, Backend, Kubernetes, Machine Learning Operations, Virtual Agents, Api Design, Model Inference, Docker
- **Published:** October 16, 2026
- **Apply:** https://www.juju.com/job/2_162650361

## About the Role

* Proven backend engineering experience delivering dependable, scalable production services.
 * Hands-on success with high-volume, latency-sensitive systems and troubleshooting distributed architectures during heavy demand.
 * Practical experience with production AI software, such as LLM or model inference, workflow orchestration, model-facing APIs, or intelligent automation.
 * Working knowledge of Python, Node.js, PyTorch, relational and non-relational data stores, Kubernetes, and Docker.
 * Experience integrating commercial or open-source language models, including platforms from OpenAI or Anthropic.
 * Strong command of API design, databases, cloud infrastructure, and scalable systems architecture.
 * Demonstrated ownership, sound engineering judgment, and accountability for outcomes in fast-moving, uncertain environments.
 * Clear communication with technical and non-technical partners, paired with a strong bias toward shipping quality software and learning from real-world usage.

## Description

* Build scalable backend infrastructure that powers AI-driven applications and enterprise automation workflows.
 * Shape model-serving and workflow coordination components that connect inference, application logic, data, and external services.
 * Tune service performance across request routing, caching, batching, streaming, and model calls with close attention to response time, capacity, availability, and spend.
 * Create durable interfaces and service contracts that allow client applications, data stores, AI components, and third-party tools to work together cleanly.
 * Establish strong operational visibility through telemetry, diagnostics, alerting, and disciplined response to production issues.
 * Diagnose issues within distributed environments, determine underlying causes, and use real-world performance data to strengthen system reliability.
 * Turn loosely defined product or operational needs into practical technical plans, then carry solutions from design through release and refinement.
 * Partner across engineering and business functions while independently driving technically ambiguous work to completion.