Senior AI platform Engineer

Senior AI platform Engineer. Location : Bangalore , Hybrid Model (3 days work from office in a week) About The Role We are looking for a Senior AI Platform Engineer to join our AI team and help build a next-generation AI-powered customer experience platform. This role focuses on designing, developing, and maintaining production-grade AI systems, including LLM integrations, RAG pipelines, AI agent workflows, and supporting infrastructure. You will work closely with architects and cross-functional teams to transform AI capabilities into scalable, reliable platform features. This role requires strong hands-on experience with production AI systems, prompt engineering, and LLM integration patterns in a fast-paced environment. Key Responsibilities Design, build, and maintain AI agent workflows and orchestration patterns (e.g., LangGraph) Develop and optimize production-grade RAG systems (chunking, retrieval pipelines, embeddings, response quality) Implement and manage LLM API integrations with retry logic, fallbacks, rate limiting, and cost optimization Build advanced prompt engineering solutions (system prompts, few-shot learning, structured outputs, versioning) Develop input validation, output filtering, and AI safety layers Implement AI observability and evaluation frameworks (tracing, regression testing, quality checks) Build data ingestion pipelines for AI systems (document processing, embeddings, vector storage) Collaborate with product and architecture teams to deliver scalable AI solutions Write clean, testable, and production-ready code (unit, integration, and AI-specific tests) Contribute to technical documentation, design docs, and operational runbooks Must-Have Skills & Experience 5+ years of software development experience Hands-on experience building AI/ML or LLM-powered systems in production Strong understanding of LLM fundamentals (tokens, embeddings, context windows, temperature, similarity search) Experience with RAG systems (indexing, chunking strategies, retrieval methods) Strong prompt engineering expertise (few-shot, structured outputs, iterative improvements) Experience with AI orchestration frameworks (LangGraph, LangChain, or similar) Hands-on experience with vector databases (pgvector, Pinecone, Qdrant, Weaviate, etc.) Strong proficiency in Python Experience working with LLM APIs (OpenAI, Claude, or similar) Understanding of AI safety concepts (prompt injection, jailbreaking, mitigation strategies) Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes) Strong analytical and problem-solving skills Good-to-Have Skills Experience with AI observability tools (LangSmith, LangFuse) Familiarity with Model Context Protocol (MCP) or similar integration patterns Understanding of fine-tuning vs prompt-based approaches Programming experience in Java Experience with event-driven systems (Kafka, RabbitMQ) Telecom domain knowledge (billing, CRM, lifecycle management) Experience building customer-facing AI products Backend development experience (Go, Node.js, Java microservices)