Forward Deployed Engineer (FDE)

Job Description

- Utilize Deep GenAI and Agentic AI experience, especially in RAG, GraphRAG, Knowledge Graphs, and semantic search. - Develop multi-agent orchestration, tool use, memory, and human-in-the-loop capabilities. - Engage in full-stack AI application development with APIs, backend, and production deployments using Python. - Build document ingestion and intelligent document processing pipelines. - Apply ML background in forecasting, prediction, anomaly detection, and fraud/analytics use cases. - Work hands-on with Azure, GCP, and ideally AWS, including AI/ML services and Kubernetes. - Implement MLOps/LLMOps practices for model lifecycle, monitoring, governance, explainability, and production readiness. - Demonstrate strong data architecture skills in large-scale pipelines, complex schemas, event-driven systems, APIs, and high-volume processing. - Define AI strategy, roadmaps, reference architectures, standards, and best practices. - Collaborate with business leaders and executives, mentor engineers, and contribute to technical design. - Take ownership of work end-to-end with minimal supervision. - Preferably have experience in finance/banking or regulated environments. - Exhibit strong communication, stakeholder management, and cross-functional leadership skills. - Strong Python skills for AI application development. - Proficiency in ML for forecasting, prediction, anomaly detection, and fraud/analytics. - Hands-on experience with Azure, GCP, and ideally AWS. - Knowledge of MLOps practices and model lifecycle. - Strong data architecture skills for large-scale pipelines and event-driven systems. - Ability to define AI strategy, roadmaps, and best practices. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.