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. You’ll 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, you’ll 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 Tech’s 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 Next.js 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.
Benefits
What we offer
Ownership of a transformative AI system redefining industrial interaction
Opportunity to lead architecture and shape a flagship product at MASS Tech
Remote-first work culture with flexible hours
Competitive salary and performance-based bonus
Profit-sharing plan
Paid time off and holiday policy
Professional development stipend