AI Native Developers

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pune 3 Years Exp Posted 68d ago

Design and develop full-stack applications for Leapswitch products from concept to production deployment
Use AI tools (Claude, Cursor, Copilot, Claude Code) daily as a core part of your development workflow – for code generation, architecture review, debugging, documentation, and testing
Integrate with cloud infrastructure - OpenStack (Nova, Neutron, Cinder, Magnum, Glance), billing, marketing, support and other APIs
Build AI/ML-powered features including RAG pipelines, LLM-based agents, predictive analytics, anomaly detection, and natural-language interfaces for infrastructure management
Develop and maintain REST/GraphQL APIs, event-driven microservices, and real-time data pipelines
Work with GPU infrastructure – understand GPU-as-a-Service and AI-as-a-Service delivery models
Collaborate cross-functionally with infrastructure, sales, and support teams to translate business requirements into technical solutions
Stay current with cloud and AI industry trends, competitive landscape and emerging technologies

Required Skills & Qualifications

Demonstrated, daily use of AI coding assistants (Claude, ChatGPT, Cursor, GitHub Copilot, Claude Code) in professional projects
Ability to effectively prompt, iterate, and validate AI-generated code, not just copy-paste, but critically evaluate and refine
Experience building applications that integrate LLM APIs (Anthropic Claude, OpenAI) – prompt engineering, function calling, structured outputs, streaming
Understanding of RAG architectures, vector databases (pgvector, Pinecone, Weaviate), and embedding models
Portfolio or examples demonstrating AI-augmented development velocity

Strong in Python and/or TypeScript/Node.js (Bun, Hono, Express, FastAPI, Django)
Frontend: React, Next.js, or Vue.js with modern UI frameworks (Tailwind, shadcn/ui)
Databases: PostgreSQL, Redis, ClickHouse, or similar; SQL fluency
Cloud-native: Docker, Kubernetes, OpenStack APIs, Terraform, Ansible
API design: REST, GraphQL, WebSockets, event-driven patterns (Kafka, RabbitMQ, webhooks)
Version control: Git, GitHub/GitLab, CI/CD (GitHub Actions, GitLab CI)

Solid understanding of cloud infrastructure concepts like virtualisation (KVM, QEMU), networking (VLANs, BGP, SDN), storage (Ceph, block/object storage), and compute
Familiarity with the IaaS/PaaS/SaaS/GPU-aaS landscape, pricing models, and competitive dynamics
Awareness of the AI/ML ecosystem - GPU hardware, inference vs. training workloads
Understanding of cloud billing, metering, and usage-based pricing models
Interest in or experience with cloud security, compliance, and data sovereignty