About ZenteiQ

ZenteiQ is building the Scientific Intelligence Infrastructure for industry — physics-native AI for engineering, manufacturing, energy, and mobility. Born at IISc Bangalore and founded by Prof. Sashikumaar Ganesan, we are one of eight startups selected by the IndiaAI Mission (MeitY) to build India's sovereign foundation models.

Most AI today is adapted from general-purpose language models. We train ours from scratch. BrahmAI, our family of scientific foundation models, learns from simulation, sensor, and research data to reason across thermal, electromagnetic, structural, and materials domains. That intelligence powers KogneX, our AI-native R&D; platform for enterprises and manufacturing, and AhamX, the talent and research OS behind our AI Hub Network of partner institutions.

We are a team of 35+ scientists, AI researchers, and engineers turning frontier research into systems that industry actually runs on.

About this Role

ZenteiQ is building agentic, Generative AI-powered systems that need to run not as demos but as production infrastructure people depend on. The platform, powered by our Scientific Foundation Model, is designed for a wide range of consumers — from government to industry to academia. This role owns the architecture decisions that determine whether our agentic AI infrastructure is trustworthy at scale: state management across distributed components, failure handling, and performance engineering that keeps cost and latency in check as the system grows more capable.

We're looking for someone who can look at a distributed system under load and know, within minutes, whether it's about to fail gracefully or catastrophically — and who has already spent a career building the muscle to make it fail gracefully. Someone who has shipped code themselves for long enough to distrust architecture that only exists on a whiteboard, and who now wants to point that instinct at one of the hardest problems in applied AI: making multi-agent, RAG-driven systems behave predictably in production.

What You'll Do Here





- Architect distributed systems and developer infrastructure that hold up under real production load.
- Prototype hands-on to prove an architecture before it becomes a standard others build against.
- Participate actively in code review, catching failure modes and design issues others may miss.
- Turn architecture decisions into technical documentation clear enough that another senior engineer could challenge the reasoning without a meeting.
- Own the tradeoffs between performance, cost, and reliability, and defend those tradeoffs with evidence.
- Define the organizational tech stack and coordinate technical direction across teams, ensuring there is no unmanaged technology sprawl.

What We're Looking For

- Demonstrated experience architecting high-performance, distributed systems and developer infrastructure that have run in production.
- Full-stack engineering depth — able to reason about and personally build across the stack, not just direct others who do.
- A track record of building systems that are trustworthy and cost-efficient under real failure conditions, with evidence to back it.
- Experience architecting end-to-end, multi-agentic GenAI/RAG pipelines — ingestion, chunking, vector search, message passing, and orchestrator patterns — that stay reliable as complexity grows.
- Robust command of design patterns, state management, and failure-handling patterns for distributed and agentic systems.
- An appetite for solving hard, ambiguous problems in distributed and agentic system design, where the right answer isn't established yet.

Tech Stack Programming Languages: Python, TypeScript, JavaScript

Frameworks & Libraries: FastAPI, Pydantic, Next.js, React, TanStack Query

AI / ML Frameworks: RAG pipelines (ingestion, chunking, retrieval), vector search & embeddings,



multi-agent orchestration frameworks

Cloud Platforms: GCP (Cloud SQL, GCS, GKE), multi-cloud patterns

Infrastructure & DevOps: Docker, Kubernetes (GKE), Kafka / Google Pub/Sub, Prometheus & structured logging, CI/CD pipelines

Databases: PostgreSQL (schema design, indexing, migrations)

Tools & Platforms: OpenAPI/Swagger, API versioning, auth patterns, SSR/SSG/CSR/ISR, HTML5, CSS3, frontend performance & bundle optimization, testing practices

Nice to Have

Experience standing up developer infrastructure or platform tooling used by other engineering teams.

Exposure to on-device or resource-constrained AI deployment.

Background contributing to or reviewing architecture for early-stage, fast-moving engineering organizations.

Formal chaos engineering or failure-injection testing experience.

Why Work with ZenteiQ

- Build AI from the ground up — Work on foundation models, agentic AI systems, and next-generation engineering intelligence rather than simply integrating existing AI tools.
- Solve meaningful engineering problems — Apply AI to real-world challenges in advanced industries where technology creates measurable impact.
- Work alongside exceptional talent — Collaborate with experienced engineers, researchers, and builders who have deep expertise in AI, distributed systems, and enterprise software.
- Own your architecture — This is a flat, low-bureaucracy environment: architecture decisions get made by whoever has the clearest thinking and the evidence to back it, not by seniority or process. You'll define the technical direction for a platform from an early stage, not inherit someone else's constraints.
- Learn continuously — You'll be exposed to cutting-edge technologies, rapidly evolving AI research, and opportunities to grow your technical expertise.
- Make a lasting impact — Your architecture decisions shape infrastructure used across government, industry, and academia, as part of India's Sovereign AI Mission and the IndiaAI Mission's Scientific Foundation Model initiative.

📌 Principal Architect (Bengaluru)
🏢 ZenteiQ.ai
📍 Bengaluru