At Nurix AI
, we are pioneering the Autopilot Enterprise
. Our conversational AI agents handle workflows, drive outcomes, and deliver measurable impact for businesses. Born from the belief that enterprises need a new playbook, we build autonomous, multilingual agents capable of complex reasoning, contextual understanding, and end-to-end workflow ownership. Backed by $27.5M in funding
from Accel, General Catalyst, and Meraki Labs
, and led by Mukesh Bansal
, we are India s first scaled enterprise AI company, delivering cutting-edge AI solutions that integrate seamlessly into workflows across industries like Retail, Insurance, Education & Home Services
. Join us in shaping the future of enterprise AI - where every interaction is smarter, faster, and human-like.
As
Principal Architect at Nurix AI
, you will be the cornerstone of our technical infrastructure, enabling our AI agents to scale reliably and securely in production. You will design and oversee distributed systems that deliver low-latency, high-availability voice and chat AI
, while meeting enterprise-grade security and compliance requirements. This is a hands-on leadership role focused on architecture, systems design, and performance engineering
- ensuring that Nurix s groundbreaking AI research translates into robust, real-world deployments.
Key Responsibilities
Systems Architecture & Scalability
- Design and evolve the
end-to-end infrastructure
supporting ASR/TTS, LLM orchestration, Agentic RAG, and self-learning workflows. - Architect
low-latency pipelines
for real-time conversational AI, ensuring sub-second response times across voice and chat. - Build
multi-cloud, distributed systems
(AWS, GCP, Azure) with elastic scaling to handle spiky workloads.
Reliability & Performance Engineering
- Define and enforce SLAs around
latency, uptime, and throughput
for AI services. - Drive observability, monitoring, and resilience strategies to handle failures gracefully.
- Optimize GPU/TPU utilization for cost-effective training and inference.
Security & Compliance
- Partner with InfoSec to embed
security-by-design
across all AI/ML workloads. - Implement controls to protect sensitive enterprise data while meeting
global compliance standards
(SOC2, ISO 27001, GDPR, DPDP).
Collaboration & Leadership
- Work closely with the Head of AI to translate cutting-edge research into
production-grade platforms
. - Provide technical mentorship to engineering teams, ensuring best practices in distributed systems and infra design.
- Evaluate and adopt emerging technologies (e.g.,
SSMs, inference optimizers like Triton, Riva, vLLM
) to stay ahead of the curve.
Required Qualifications & Skills
-
10 - 15 years of experience
in large-scale systems architecture, with at least 5 years in principal/architect-level roles. - Proven expertise in
distributed systems, cloud-native architectures, and real-time pipelines
. - Hands-on experience with
containerization, orchestration (Kubernetes), and microservices
. - Strong background in
scalable ML infrastructure
, including model serving, GPU/accelerator utilization, and CI/CD for ML. - Demonstrated ability to architect systems with
low latency (.
Experience inconversational AI, speech systems, or real-time inference workloads.Deep knowledge ofMLOps platforms(Kubeflow, MLflow, VertexAI, SageMaker).Familiarity withstate-of-the-art inference optimizationframeworks (e.g., Triton, Nvidia Riva, vLLM, SGLang).Open-source contributions or patents in distributed systems, infra, or ML tooling.
