Design and implement end-to-end RAG systems and AI interfaces
Develop vector search solutions and custom embedding approaches
Create AI feedback loops and monitoring systems
Implement AI caching strategies and security middleware
Design and optimize LLM system architectures
Build AI error handling and recovery UIs
Develop multi-agent systems for complex workflows
Implement AI data validation pipelines and quality monitoring
Create AI security measures including prompt injection prevention
Help scale and optimize AI applications

Required Qualifications
Awareness and hands-on experience with LLM-based applications
12+ years of experience in full-stack development
Experience with production LLM systems
Masters or PhD in Computer Science, AI/ML, or related field
Expert-level programming proficiency in multiple languages (Python, Java, JavaScript)
Experience with cloud platforms (AWS, Azure, GCP)
Expertise in GenAI architectures (RAG systems, vector search,



prompt engineering)
Experience with vector databases and embedding technologies
Knowledge of event-driven architectures
Familiarity with AI monitoring tools and testing frameworks

Nice to have
Active contributor to GenAI community (publications, contributions to open-source projects, blog, personal GenAI projects, etc.)
Advanced certifications in GenAI development
Experience with hybrid LLM architectures and model deployment
Expertise in multi-agent system architecture
Implementation of AI cost optimization frameworks
Knowledge of AI data versioning systems

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Full Stack Developer Genai Systems Pune
🏢 Crisil
📍 Pune