Join AlvioLabs as a Senior Backend Engineer to build and scale the robust infrastructure powering our Enterprise Agentic AI Platform. You'll architect high-performance APIs, implement AI agent orchestration systems, and ensure our platform can handle enterprise-scale workloads with reliability and security.About Alvio:Alvio is an enterprise-grade Agentic AI platform that enables businesses to accomplish complex tasks through AI automation. Our platform integrates multiple LLM providers, manages containerized AI agents, and provides seamless browser automation, file management, and API integrations.Key Responsibilities:API Development & Architecture: Design and implement RESTful APIs using FastAPI 0.115+ Build scalable microservices architecture with proper separation of concerns Implement authentication and authorization using Supabase Auth with JWT Create comprehensive API documentation with OpenAPI/Swagger Optimize API performance and implement caching strategies AI Agent System Development: Build AI agent orchestration and management systems Implement tool execution frameworks with proper sandboxing Develop agent versioning and configuration management Create workflow execution engines for multi-step AI tasks Implement real-time agent communication and status updates Database & Data Management: Design and optimize PostgreSQL schemas with Supabase Implement Row Level Security (RLS) policies for multi-tenant architecture Create and manage database migrations with proper versioning Optimize queries and implement proper indexing strategies Handle large-scale data processing and ETL operations Integration & External Services: Integrate multiple LLM providers (Anthropic, OpenAI, Groq, AWS Bedrock) Implement webhook systems and event-driven architectures Build integrations with external APIs and services (Composio, MCP) Manage credential encryption and secure API key storage Implement rate limiting and quota management systems Performance & Scalability: Implement async/await patterns for high-concurrency operations Design caching strategies using Redis for optimal performance Build background job processing with Dramatiq workers Implement proper error handling and retry mechanisms Monitor and optimize system performance and resource usage Required Skills & Technologies:Core Backend Development: Expert-level Python 3.11+ with comprehensive type hints FastAPI framework with dependency injection patterns Async/await programming and concurrent processing RESTful API design and microservices architecture Database design and optimization (PostgreSQL) AI/ML Integration: Experience with LLM APIs and multi-provider integration Understanding of AI agent architectures and tool systems Knowledge of prompt engineering and structured outputs Experience with AI observability and monitoring (Langfuse) Familiarity with AI model deployment and scaling Database & Infrastructure: Advanced PostgreSQL with complex queries and optimization Supabase platform experience (preferred) or similar BaaS Redis for caching and session management Database migration management and versioning Understanding of ACID properties and transaction management Security & Authentication: JWT token validation and user session management API security best practices and input validation Encryption and secure credential storage Understanding of OAuth 2.0 and authentication flows Experience with enterprise security compliance DevOps & Deployment: Docker containerization and multi-stage builds CI/CD pipeline setup and management Cloud deployment (AWS/GCP) and infrastructure management Monitoring and logging implementation (Sentry, Prometheus) Performance profiling and optimization Technical Stack You'll Work With: Backend: Python 3.11+, FastAPI 0.115+, Pydantic Database: Supabase (PostgreSQL), Redis 5.2+ AI/ML: LiteLLM 1.72+, multiple LLM providers Queue/Jobs: Dramatiq 1.18+, background processing Monitoring: Langfuse, Sentry, Prometheus, Structlog Security: JWT, encryption (Fernet), credential management Tools: Docker, Git, pytest, black, mypy Preferred Qualifications: Experience with AI/ML model serving and inference Knowledge of containerized application deployment Familiarity with event-driven architectures and webhooks Experience with high-traffic, enterprise-scale applications Background in fintech or regulated industries Contributions to open-source Python projects Experience with GraphQL or real-time subscriptions Key Projects You'll Work On: AI agent execution engine with tool orchestration Multi-tenant authentication and authorization system Real-time agent communication and status updates Integration platform for external AI tools and services Performance optimization for high-concurrency workloads What We Offer: Cutting-edge AI technology stack and tools Professional development budget and conference attendance Comprehensive health insurance and wellness benefits Opportunity to architect the future of AI automation Job Types: Full-time, Permanent Pay: ₹60,000.00 - ₹100,000.00 per month Benefits: Health insurance Internet reimbursement Paid sick time Experience: Redis: 5 years (Preferred) Dramatiq: 5 years (Preferred) Docker: 5 years (Preferred) FastAPI: 5 years (Preferred) Pydantic: 5 years (Preferred) Supabase (PostgreSQL): 5 years (Preferred) Work Location: In person Speak with the employer +91 8006446541
Join AlvioLabs , the creators of a cutting-edge Enterprise Agentic AI Platform that's revolutionizing how businesses accomplish real-world tasks through AI automation. We're seeking a skilled AI DevOps Engineer to manage and scale our sophisticated infrastructure supporting AI agents, containerized environments, and enterprise-grade deployments.About Alvio:Alvio is an enterprise-grade Agentic AI platform that helps businesses accomplish real-world tasks with unprecedented efficiency. Our platform combines powerful AI capabilities with browser automation, file management, web crawling, and seamless integrations - all through natural conversation interfaces.Key Responsibilities:Infrastructure & Container Management: Design and maintain Docker-based containerized environments for AI agent execution Manage multi-stage Docker builds and optimize container performance Implement and maintain Kubernetes clusters for production workloads Configure auto-scaling policies for dynamic workload management AI/ML Infrastructure: Deploy and manage LLM integrations (Anthropic, OpenAI, Groq, AWS Bedrock) Implement monitoring for AI model performance and token usage Manage GPU resources and optimize inference workloads Set up A/B testing infrastructure for model comparisons Cloud & Database Operations: Manage Supabase PostgreSQL databases with Row Level Security (RLS) Implement Redis caching strategies for high-performance applications Configure and maintain cloud infrastructure (AWS/GCP) Handle database migrations and backup/recovery procedures CI/CD & Automation: Build and maintain GitHub Actions pipelines for automated deployments Implement Infrastructure as Code using Terraform/CloudFormation Set up monitoring and alerting systems (Prometheus, Grafana, Sentry) Manage secrets and environment configurations across multiple environments Security & Compliance: Implement enterprise-grade security standards and compliance measures Configure SSL/TLS, security headers, and rate limiting Manage API key rotation and credential encryption Conduct security audits and vulnerability assessments Required Skills & Technologies:Core DevOps: Docker & Docker Compose (production experience) Kubernetes orchestration and management CI/CD pipelines (GitHub Actions preferred) Infrastructure as Code (Terraform, CloudFormation) Cloud Platforms: AWS/GCP cloud services and architecture Database management (PostgreSQL, Redis) Load balancing and auto-scaling configurations CDN and edge computing setup AI/ML Infrastructure: Experience with LLM deployment and scaling GPU resource management and optimization Model serving frameworks and APIs AI observability and monitoring tools Programming & Scripting: Python 3.11+ for automation scripts Bash/Shell scripting for system administration YAML/JSON for configuration management Basic understanding of TypeScript/Node.js Monitoring & Security: Prometheus, Grafana, Sentry integration Log aggregation and analysis (ELK stack) Security scanning and vulnerability management Secrets management (Vault, AWS Secrets Manager) Preferred Qualifications: Experience with AI/ML model deployment at scale Knowledge of FastAPI and Python web frameworks Familiarity with Supabase or similar BaaS platforms Experience with enterprise security compliance Background in fintech or regulated industries What We Offer: Cutting-edge AI technology stack Professional development budget Health insurance and wellness benefits Opportunity to shape the future of AI automation Job Types: Full-time, Permanent Pay: ₹60,000.00 - ₹100,000.00 per month Benefits: Health insurance Internet reimbursement Paid sick time Experience: Database management: 4 years (Preferred) AWS: 4 years (Preferred) AI: 4 years (Preferred) Work Location: In person Speak with the employer +91 8006446541