Senior AI Engineer, AI Engineering
Core
Lead ML engineering team to execute AI/ML strategy, enabling business growth and enhancing customer experience through secure, scalable software solutions.
Role type
Senior IC machine learning engineering lead (LLM/Agentic systems)
Builds
Multi-agent intelligence frameworks, multi-modal AI pipelines, RAG/Graph-RAG systems, transformer-based models, and LLMOps/MLOps pipelines
Domain
Financial services / Generative AI / Multi-modal AI
Deliverable
production ML models
Required skills
Multi-agent frameworks (LangGraph, CrewAI, AutoGen), Multi-modal transformers (BERT, CLIP, LLaVA, T5, Whisper), RAG and Graph-RAG systems, Vector stores and knowledge graphs (Neo4j, AWS Neptune), Transformer-based model development (NLP, vision-language, sequential prediction), Python backend services for inference orchestration, LLMOps and MLOps pipelines (Databricks, MLflow, feature stores), Statistical modeling and traditional ML techniques, Responsible AI practices
Preferred skills
Data visualization tools (Tableau, Power BI), Cloud computing services (AWS, Azure, GCP)
Technologies
LangGraph, CrewAI, AutoGen, BERT, CLIP, LLaVA, T5, Whisper, Neo4j, AWS Neptune, Hugging Face, PyTorch, TensorFlow, Databricks, MLflow
Responsibilities
Implement multi-agent intelligence frameworks for adaptive decision-making; Design and operationalize multi-modal AI pipelines; Build scalable RAG and Graph-RAG systems; Develop and productionize transformer-based models; Implement advanced Python-based backend services for inference orchestration; Establish end-to-end LLMOps and MLOps pipelines; Apply traditional AI/ML and statistical modeling techniques; Engineer state and memory management subsystems; Implement Responsible AI practices; Continuously research and productionize innovations in multimodal transformers and agentic orchestration
Seniority
Senior, hands-on IC with team leadership
