Principal Engineer (NodeJS/Python) - Bengaluru

About the role

Live2.ai is hiring a Principal Engineer in Bengaluru to own its core system architecture for an AI-native platform serving Fortune 500 brands. This is a hands-on individual contributor role focused on distributed systems, tenant isolation, reliability and correctness, working alongside the Head of Engineering with no direct reports. The position is on-site in Bengaluru.

Key responsibilities

• Own core architecture for tenant isolation, data models, distributed processing, correctness and traceability.
• Design systems for high-volume ingestion, processing, search, analytics and AI workloads.
• Own decisions on service boundaries, APIs, storage, caching, queues and asynchronous processing.
• Co-own architecture decision records with written reasoning and multiple signers.
• Set technical standards through design reviews and practical examples.
• Handle escalations on production correctness, performance, reliability and architecture.
• Work with Site Reliability Engineers on availability, recovery, observability and isolation guarantees.
• Help tech leads and senior engineers develop technical judgment, prototype difficult problems, and work with the Head of Engineering on technical depth and correctness.

Required profile

• Around 8+ years of experience building and operating production systems, with continued responsibility after launch.
• Ability to make and defend architectural decisions on cost, complexity and operational risk, and to challenge a founder or Head of Engineering with evidence-based reasoning.
• Continues to write production code regularly.
• Nice to have: regulated or audited environment experience, cryptographic integrity experience, AI/LLM component experience, enterprise customer escalations, and a previous Staff or Principal Engineer role at a similar-stage company.

Required skills

• Distributed systems: service boundaries, queues, asynchronous processing, event-driven architectures, retries, idempotency, concurrency, consistency and failure recovery.
• PostgreSQL with pgvector, indexing, partitioning, transactions, query optimisation, migrations and multi-tenant isolation.
• High availability, fault tolerance, observability, disaster recovery and safe reprocessing.
• Authentication, authorisation, RBAC, tenant isolation, encryption and auditability.
• Production AI/LLM components: model abstraction, asynchronous inference, evaluation, versioning, cost controls and traceability.
• Stack: TypeScript/Node.js, Python, PostgreSQL, OpenSearch, Redis, GCP, Kubernetes/GKE, Docker; deep fundamentals matter more than every technology.