- Deep GenAI / LLM experience, especially RAG, GraphRAG, Knowledge Graphs, semantic search, vector databases

- Strong Agentic AI experience: multi-agent orchestration, MCP, tool use, memory, human-in-the-loop

- Robust Python / full-stack AI application development with APIs, backend, and production deployments

- Experience building document ingestion / intelligent document processing pipelines

- Strong ML background: forecasting, prediction, anomaly detection, fraud/analytics use cases

- Hands-on Azure, GCP, and ideally AWS, including AI/ML services and Kubernetes

- Experience with MLOps / LLMOps, model lifecycle, monitoring, governance, explainability, and production readiness

- Strong data architecture skills: large-scale pipelines, complex schemas,



event-driven systems, APIs, high-volume processing

- Senior enough to define AI strategy, roadmaps, reference architectures, standards, and best practices

- Able to work directly with business leaders and executives, while also mentoring engineers and going deep into technical design

- Comfortable owning work end-to-end with minimal supervision

- Preference for experience in finance/banking or regulated environments

- Strong communication, stakeholder management, and cross-functional leadership

📌 FDE (Bengaluru)
🏢 Ascendion Engineering
📍 Bengaluru