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Senior Full Stack Engineer

Mass Tech LLC

Job Location:

Greensboro, NC - USA

Monthly Salary: Not provided by the employer

Experience Required: 5-8years

Posted: 13 September 2026 (2 days ago)

Application Deadline: 11 December 2026

Vacancies: 1 Vacancy

Job Summary

Summary

As a Senior Full Stack Engineer at MASS Tech you will play a pivotal role in shaping the future of intelligent equipment interaction through the development of a cutting-edge Google-native AI platform. Youll lead the end-to-end design and implementation of a scalable secure and high-performance system that leverages RAG (Retrieval-Augmented Generation) QR-based workflows and Gemini LLMs to transform how field technicians and operators engage with industrial equipment. By integrating real-time data technical documentation and generative AI youll help build a unified intelligence layer that enhances operational efficiency reduces downtime and empowers users with contextual accurate insights. This role sits at the intersection of cloud engineering AI systems and product innovation offering a unique opportunity to influence both technical architecture and user experience in a mission-driven AI-first environment.

Responsibilities

Own the full lifecycle of MASS Techs Firestore-based vector RAG platform from system design to deployment and maintenance.
Design and implement serverless ingestion pipelines that extract process and embed technical PDFs using Vertex AI for semantic indexing.
Develop and optimize Firestore-native vector search capabilities with equipment-specific filtering for precise context-aware retrieval.
Build and maintain a responsive secure frontend for public QR access interactive chat interfaces and real-time equipment dashboards.
Architect and manage scalable APIs using Cloud Run and Firebase Functions to support high-traffic low-latency use cases.
Integrate Vertex AI Gemini to generate real-time safe and citation-aware responses within the user interface.
Collaborate closely with product design and AI teams to refine prompt engineering user experience flows and context management.
Implement observability monitoring and performance optimization strategies to ensure low latency and cost-effective operation across the stack.

Requirements

Requirements:

5 years of professional experience in software engineering with demonstrated expertise in backend systems cloud platforms and frontend development.
Proven experience with Google Cloud Platform (GCP) including Vertex AI Firestore Cloud Functions and Firebase.
Hands-on experience building or integrating LLM-powered RAG systems embedding pipelines or vector search solutions.
Strong grasp of scalable system design CI/CD practices API architecture and observability tooling.
Excellent communication and documentation skills particularly when explaining AI/ML system behavior and constraints.
Experience working in cross-functional teams with product managers designers and AI researchers.
Preferred: Prior experience developing software for manufacturing industrial equipment or field operations environments.