Senior DevOps Engineer

5 days ago

Chennai, Tamil Nadu, India Zudu AI Full time
About the Role

We are seeking a highly skilled DevOps Engineer to design, implement, and manage our AI-driven telephony and voice automation platform. You will be responsible for end-to-end ownership of our infrastructure, ensuring seamless interaction between our AI layer, telephony systems (Twilio, Plivo, Genesys, etc.), knowledge base, and third-party APIs. This includes real-time call handling, queueing, AI model hosting, vector databases, caching, and advanced CI/CD pipelines. You'll play a critical role in scaling and securing our environment as we grow.

Key Responsibilities

1. Infrastructure Architecture & Management

- Design and maintain multi-tenant, cloud-based infrastructures (AWS, Azure, or GCP) with a focus on high availability and fault tolerance.
- Architect solutions that integrate real-time call processing, voice APIs, AI inference (e.g., GPT-based), and knowledge bases (vector DB, function calls, etc.).
- Manage both single-instance and multi-tenant setups, handling tasks like authentication, data storage, and security.

1. CI/CD Pipeline & Automation

- Set up robust CI/CD pipelines for microservices, ensuring quick and reliable deployments of AI/ML models, API services, and front-end components.
- Implement best practices for Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar tools.

1. Containerization & Orchestration

- Deploy, manage, and scale Docker or Kubernetes clusters to host AI processing, streaming, caching, and web services.
- Optimize container images, orchestrate updates/rollbacks, and troubleshoot performance bottlenecks in a microservices environment.

1. Real-Time Voice & Queueing Systems

- Integrate telephony providers (Twilio, Plivo, Genesys, etc.) with queueing mechanisms (RabbitMQ, Kafka, or built-in Twilio queues) to handle high concurrency (e.g., thousands of calls/minute).
- Work closely with the engineering team to ensure minimal latency and high reliability in voice-based AI workflows.

1. Monitoring & Observability

- Set up comprehensive logging, monitoring, and alerting solutions (Prometheus, Grafana, Datadog, ELK stack, etc.) to ensure 24/7 uptime, quick issue resolution, and detailed performance insights.
- Conduct regular load testing, stress testing, and capacity planning to handle scaling demands.

1. Security & Compliance

- Implement best practices for network security, encryption, secrets management, and access control.
- Stay updated on compliance requirements (e.g., GDPR, ISO27001, HIPAA if relevant) and ensure our systems align with security standards.

1. Collaboration & Leadership

- Work alongside AI engineers, back-end developers, and product stakeholders to translate business needs into technical requirements.
- Provide guidance to junior engineers, help shape DevOps culture, and drive continuous improvement in processes and tooling.

1. Research & Innovation

- Stay abreast of industry trends and emerging technologies (e.g., SurrealDB, vector databases, serverless patterns).
- Evaluate and prototype new tools, frameworks, and services (similar to VAPI, RetellAI, Bland AI) that can enhance platform reliability, performance, or scalability.

Required Skills & Experience

- Technical Background: Bachelor's or Master's in Computer Science, Engineering, or related field (or equivalent experience).
- Cloud Expertise: Hands-on with AWS, Azure, or GCP, including compute, storage, and managed services for container orchestration.
- Automation & IaC: Proficient in Terraform, Ansible, CloudFormation, or similar IaC tools for repeatable infrastructure deployments.
- Containers & Orchestration: Deep knowledge of Docker, Kubernetes (EKS, AKS, GKE), Helm, and associated ecosystem.
- Telephony/VoIP: Experience integrating and scaling solutions with Twilio, Plivo, or similar cloud telephony services.
- AI/ML Deployment: Familiarity with serving large language models, knowledge bases (vector DB), and real-time inference pipelines.
- Monitoring & Logging: Experience with ELK Stack, Prometheus + Grafana, or other enterprise monitoring tools.
- Scripting & Programming: Solid scripting skills in Bash/Python. Knowledge of back-end languages (Node.js, Go, Python) is a plus.
- Security: Understanding of networking, certificates, secrets management, and overall DevSecOps best practices.
- Problem-Solving: Ability to diagnose complex issues spanning multiple systems (network, storage, code, telephony) under pressure.

Preferred Qualifications

- Prior experience with serverless frameworks, microservices, or edge computing architectures.
- Familiarity with advanced caching strategies (Redis, Memcached) and streaming solutions (Kafka, NATS).
- Hands-on experience implementing high-availability, multi-region, or hybrid cloud systems.
- Knowledge of SurrealDB, FaunaDB, or other modern database solutions used for AI-driven knowledge bases.

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