Prospect:

As an AI SDE III (Full Stack) at Hiver, you will work end-to-end across frontend, backend, and AI systems to craft the next generation of collaborative email, automation, and AI-powered customer service workflows.

You will own major product surfaces, architect scalable systems, and bring intelligent experiences to life in the UI while ensuring reliability for 5M+ emails processed daily across thousands of active users.

Key Responsibilities

What you will do?

Full-Stack Product Engineering
Build intuitive, performant UIs in React/Vue for email collaboration, analytics, and AI-assisted workflows.
Ship features end-to-end across frontend, backend APIs, domain models, and data pipelines.
Integrate AI suggestions, copilots, and retrieval-based workflows seamlessly into the product experience.
Collaborate closely with design & product to deliver polished, consumer-grade UX.

Backend, Distributed Systems & AI
Scale backend systems to handle rapidly growing traffic and AI workloads.
Build low-latency inference and retrieval endpoints, caching layers, and model-serving pipelines.
Improve reliability, resiliency, and performance across monolith and microservices environments.
Work with Kafka/RabbitMQ to build high-volume, event-driven data flows.




Partner with ML/AI teams to deploy embeddings, rerankers, RAG systems, and evaluation workflows.

Data, Security & Observability
Implement secure, compliant data handling for structured/unstructured customer data.
Own observability across the stack tracing, metrics, dashboards, feature flags, SLOs.
Lead debugging of complex issues across frontend, backend, infra, and model pipelines.
Drive postmortems, root-cause analysis, and process improvements.

What were looking for?

Must Have:
5+ years building and scaling production systems end-to-end.
Solid backend expertise in Go/Java/Python.
Solid proficiency in React/Vue and TypeScript.
Deep understanding of distributed systems, concurrency, performance, and resiliency.
Experience with SQL plus familiarity with NoSQL/caches.
Exposure to production model serving (embeddings, RAG, inference APIs).
Solid fundamentals in cloud infra (AWS preferred), containers, and CI/CD.

Nice to Have:
Experience with vector databases (pgvector, Pinecone, OpenSearch).
Familiarity with vLLM, Triton, TorchServe, or model quantization.
OpenTelemetry, feature flag platforms, A/B testing systems.
Prior experience building B2B SaaS or email/collaboration products.

📌 Ai Sde 3 Full Stack Bengaluru
🏢 Hiver
📍 Bengaluru