Lead DevOps & Platform Engineer

About Us

At Nurix AI, we envision a world powered by super-intelligent AI agents that transform how businesses engage with customers. Our cutting-edge AI agents do more than just solve problems—they create opportunities. From suggesting next purchases to boosting revenue while maintaining customer satisfaction, to analyzing vast datasets for actionable insights, our technologies shape business and product strategies. By resolving queries with precision and delivering highly personalized interactions, we redefine the customer experience and drive measurable impact.

Nurix.ai is at the forefront of AI innovation, developing cutting-edge AI and LLM solutions to enhance productivity and automation. Backed by $27.5M in seed funding, we are building next-gen AI-driven applications that redefine human-machine collaboration as India’s first scaled AI services company. Backed by robust funding, we are a vibrant, high-ownership team set on redefining technological boundaries.

Join us in building the future, where every interaction is smarter, faster, and more impactful.

Role Overview

We are seeking a versatile Lead DevOps & Platform Engineer who brings a strong blend of core application engineering and cloud/infrastructure platform leadership.

This role requires someone who has built and shipped software as a core application developer (in runtimes like Python, Java, Go, or Node.js) and later transitioned into or spearheaded a DevOps/Infrastructure charter. You will bridge the gap between application development and cloud operations—ensuring our AI agents and SaaS platform are architected for extreme scale, resiliency, and speed of delivery.

If you are a hands-on leader who can "lead by example," write clean code, and design high-availability infrastructure from the ground up, we’d love to hear from you.

Key Responsibilities

1. Cloud Infrastructure & Platform Architecture (MUST)

• Design, implement, and manage scalable cloud infrastructure primarily on AWS (with exposure to GCP/Azure).

• Build ground-up multi-region network architectures for enterprise workloads, securing networks into layered trust zones (subnets, VPC peering/privatelinks, NAT gateways at scale).

• Architect high-availability (HA) and disaster recovery (DR) setups aligned with strict RPOs and RTOs.

• Design compute, storage, and networking layers for complex, high-throughput systems (microservices, data pipelines, LLM inference endpoints, and vector databases).

• Automate infrastructure management end-to-end using Infrastructure-as-Code (IaC) tools (e.g., Terraform, CloudFormation).

2. Containerization & Orchestration (MUST)

• Set up, monitor, and manage large-scale Kubernetes (EKS/GKE) clusters for seamless deployment of microservices and AI workloads.

• Manage persistent volume configurations for dynamic pods at scale.

• Implement best practices for networking policies, service meshes, and ingress control within Kubernetes.

3. Engineering & Technical Leadership (MUST)

• Leverage your application engineering background (Python, Java, Node.js, Go, etc.) to review developer architectures, optimize backend performance, and build internal platform tooling.

• Act as a bridge between core product engineering and infrastructure, ensuring applications are designed natively for auto-scaling and cloud reliability.

• Provide technical mentorship to engineers on deployment strategies, distributed debugging, and cloud-native development practices.

4. Performance Monitoring & Troubleshooting

• Implement robust observability and telemetry frameworks (APM, distributed tracing, metrics, logging) to track system health and AI model runtime performance.

• Lead root-cause analysis (RCA) for critical incidents and drive proactive system fixes to eliminate downtime.

5. CI/CD & Security (Good to Have)

• Oversee and optimize existing CI/CD automation and deployment workflows to maintain high developer velocity.

• Integrate basic security scanning (SAST/DAST) and ensure general alignment with security and compliance standards.

Skills & Qualifications

• Experience: 8–12+ years total experience in software engineering and infrastructure management, ideally within early-stage to growth-stage startups or AI/SaaS companies.

• Dual Engineering Background: Proven track record having spent time as a Lead Backend/Software Engineer (Python, Java, Node.js, Go) before leading a DevOps / Infrastructure / Platform Engineering charter.

• Cloud & K8s Mastery: Heavy hands-on experience designing HA/DR cloud architectures on AWS/GCP and orchestrating Kubernetes clusters at scale (CKA certification is a plus).

• Startup Mindset: Comfortable wearing multiple hats, working in fast-paced environments, and driving systems from 0 to 1 and 1 to 10.

• Leadership: Strong hands-on technical leader who "leads by example"—capable of diving deep into code, network configs, and architectural whiteboarding.