Principal Engineer

The ideal candidate should have 8 years of backend engineering experience with deep expertise in LLM-powered systems, real-time backend infrastructure, and scalable B2C product architecture. This role demands strong technical ownership, architectural leadership, and the ability to build highly reliable, production-grade AI systems at scale Top 3 Daily Responsibilities: %CF; Design and scale AI session pipelines including LLM orchestration, prompt engineering, multimodal processing, and response delivery for wearable AI systems. %CF; Own backend architecture on GCP including WebSocket services, OTA firmware delivery, push notification systems, and session management infrastructure.

%CF; Lead architectural decisions, engineering standards, and reliability practices across next-generation AI smart glasses platforms. Minimum Work Experience Required: %CF; 8 years of backend engineering experience with strong distributed systems expertise. %CF; 3 years in a Principal Engineer, Staff Engineer, or equivalent technical leadership role.

%CF; Proven production experience building and scaling LLM-powered systems and real-time backend infrastructure. %CF; Demonstrated ownership of large-scale B2C deployments including production reliability and incident management. Top 5 Skills You Should Possess: %CF; Strong expertise in LLM-powered architectures including prompt engineering, RAG pipelines, tool calling, multimodal AI, and streaming inference systems.

%CF; Deep hands-on experience with Python and Node.js for scalable backend development and code quality leadership. %CF; Strong understanding of real-time backend systems including WebSocket services, streaming pipelines, and low-latency media/audio processing. %CF; Experience designing scalable backend infrastructure on cloud platforms (preferably GCP).

%CF; Strong architectural and system design capabilities with expertise in reliability, scalability, and observability engineering. Full-Stack & System Awareness: %CF; Strong knowledge of the modern LLM ecosystem, including model capabilities, context-window tradeoffs, token economics, and emerging architectures. %CF; Familiarity with Kubernetes (GKE), PostgreSQL, BigQuery, Firebase, and cloud-native infrastructure patterns.

%CF; Understanding of AI backend pipelines involving speech recognition, visual understanding, and multimodal inference. %CF; Exposure to IoT or connected-device ecosystems including OTA delivery, BLE-connected architectures, and device-state management. Leadership & Strategic Capabilities: %CF; Ability to lead architecture reviews and define engineering standards across backend and AI systems.

%CF; Strong technical mentorship and code review expertise across Python and Node.js ecosystems. %CF; Ownership mindset with the ability to drive projects from architecture design to production deployment. %CF; Strong collaboration skills across AI, firmware, product, infrastructure, and wearable engineering teams.

Bonus Points For: %CF; Hands-on experience with Gemini, Vertex AI, or advanced GCP AI services. %CF; Experience building multimodal AI systems integrating audio, camera, and conversational interfaces. %CF; Strong understanding of token cost optimization, metering systems, and LLM cost-to-quality tradeoffs.

%CF; Knowledge of Pub/Sub systems (Kafka, RabbitMQ, GCP Pub/Sub) and distributed systems architecture. %CF; Experience working with Agentic AI systems and next-generation AI orchestration frameworks What You’ll Be Creating: %CF; A scalable AI and backend architecture powering India’s next-generation AI smart glasses platform. %CF; Real-time multimodal AI experiences combining voice, camera intelligence, and conversational AI.

%CF; Highly reliable backend systems optimized for large-scale B2C deployment across India. %CF; Engineering standards and platform foundations for future AI wearable products. %CF; A robust AI infrastructure balancing latency, scalability, reliability, and token efficiency.

Job Function: %CF; AI Backend Architecture & System Design %CF; LLM Infrastructure & Multimodal AI Engineering %CF; Real-Time Systems & Streaming Infrastructure %CF; Distributed Systems & Cloud Engineering %CF; Technical Leadership & Engineering Excellence Education: %CF; B.E. / B.Tech / M.E. / M.Tech in Computer Science, Engineering, Electronics, or related fields.

%CF; Equivalent hands-on product engineering experience with a strong delivery track record is highly valued