Voice AI Platform Engineer
1 week ago
Job Description-Must have skills required: Distributed Systems, EKS, Kubernetes, Cloud (AWS/Azure/GCP)Good to have skills : Python, FastAPI, PostgreSQL, TerraformWe're looking for a Senior Software Engineer who can architect and build robust infrastructure systems that power our voice AI platform. You'll be the backbone of our technology, ensuring our systems can handle massive scale while maintaining high performance and reliability.🚀 Your work will involve:Own end-to-end product development – from requirement gathering and architecture design to implementation and launch, you'll shepherd features through their complete lifecycle.Build for massive scale – develop systems that can handle hundreds of thousands of calls per day with high reliability and performance.Innovate through research – stay current with cutting-edge technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge.Architect distributed systems – design robust, scalable infrastructure that can handle our growing customer base and evolving product requirements.Optimize for performance – identify and resolve bottlenecks to ensure our voice AI delivers natural, real-time conversations without latency issues.🚀 Why This Role RocksYou'll have a front-row seat to building and scaling cutting-edge voice AI infrastructure.You'll get to work on system architecture, performance optimization, and scalability solutions.You will be implementing infrastructure that powers conversations with some of India's biggest enterprises (Our voice AI technology is vetted by technical leaders at companies like Paytm).You'll have direct impact on product reliability, performance, and the company's technical trajectory.You'll build mission-critical systems that enable hundreds of thousands of AI conversations daily.✅ QualificationsWe're Looking For 5+ years in backend/platform/infrastructure engineering with distributed systems experienceDeep hands-on experience with Kubernetes (EKS, GKE) including operators, custom resources, and cluster managementProficiency in cloud platforms (AWS preferred, GCP) with infrastructure-as-code (Terraform, Cloud Formation)Expertise in monitoring and observability (Prometheus, Grafana, ELK stack)Solid programming skills in Python (FastAPI, asyncio), Go, or similar systems languagesSystems & Performance Experience building high-throughput, low-latency systems (preferably real-time applications)Strong grasp of systems design, caching strategies (Redis), and message queues (Kinesis, SQS)Database expertise (PostgreSQL, Redis)Understanding of networking, service mesh, and security best practicesBonus: MLOps & AI Infrastructure Experience with ML model deployment, versioning, and monitoring in productionBackground in GPU orchestration for AI workloads (NVIDIA GPUs, CUDA optimization)Knowledge of real-time audio processing, WebRTC, or voice/video streaming systemsExperience with ML frameworks (PyTorch, TensorFlow) and inference optimizationPrevious work on multi-tenant or single-tenant SaaS platformsStartup Mindset.You've built, broken, and fixed systems in production at scaleComfortable with fast-paced environment where you'll own critical infrastructure decisionsCollaborative approach - you work well with AI teams, product, and foundersGrowth-minded and excited about scaling infrastructure for rapid business growth
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