Senior AI Engineer

Overview

CloudAngles Digital Transformation is building a next-generation AI-powered code editor that transforms how developers write, understand, and collaborate on code. We are looking for a Senior AI Engineer who will design and implement AI-native capabilities deeply embedded into the developer workflow.

This role sits at the intersection of AI/LLMs, developer tooling, and real-time systems. You will work closely with Full Stack and Platform Engineers to architect intelligent code assistance features that are fast, reliable, and production-ready.

Required

Technical Skills

• 5–8 years of software engineering experience with strong proficiency in Python
• 3+ years of hands-on experience working with LLMs and their APIs (OpenAI, Anthropic, Llama, etc.)
• Strong understanding of code editors / IDE architectures (VS Code, IntelliJ, or similar)
• Hands-on experience with Language Server Protocol (LSP), ASTs, and code analysis
• Experience with prompt engineering, context optimization, and RAG systems
• Proficiency with vector databases (Pinecone, Weaviate, Chroma, or similar)
• Experience building low-latency, real-time systems (WebSockets, streaming responses)
• Strong understanding of distributed systems, caching, and performance optimization
  
  

• Design and implement LLM integration architectures for code completion, generation, and editing
• Build prompt engineering frameworks with context management for large, multi-file codebases
• Implement retrieval-augmented generation (RAG) for codebase-aware AI suggestions
• Develop semantic code understanding using ASTs, static analysis, and LSP
• Build agent-based workflows for tasks such as refactoring, debugging, and code review
  
  

• Develop AI-assisted real-time editing and collaboration features
• Build inline AI chat interfaces, code explanations, and contextual actions
• Implement AI-powered refactoring, diff handling, and review workflows
• Enable intelligent code navigation and semantic search
  
  

• Optimize LLM inference latency for real-time usage
• Implement caching strategies for embeddings and completions
• Build token usage optimization and AI cost-control mechanisms
• Implement streaming responses and graceful fallback strategies
  
  

• Design intuitive UX flows for AI-assisted coding
• Enable customization of AI behavior through preferences and fine-tuning
• Implement telemetry and analytics to monitor usage and model performance
• Build extensibility frameworks for plugins and third-party integrations
• Ensure security best practices around AI usage (PII handling, prompt injection)
  
  

• Experience with fine-tuning techniques (LoRA, QLoRA, PEFT)
• Familiarity with agentic frameworks (LangChain, LlamaIndex, AutoGen)
• Experience with Electron or Tauri for desktop applications
• Knowledge of compiler concepts, static analysis, or program synthesis
• Exposure to observability tools (OpenTelemetry, Prometheus, Grafana)
• Contributions to open-source AI or developer tooling projects
  
  

Experience with billing, metering, or usage-based AI systems