Senior AI Engineer

Project description

We are looking for AI Engineers for a strategic initiative to build Agentic AI use cases around Trading Surveillance.

Responsibilities

• Design, develop, and maintain full-stack Python applications with modern frontend frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) systems for AI applications
• Create and implement efficient vector databases and knowledge stores
• Develop APIs that connect frontend interfaces with backend AI services
• Implement and maintain CI/CD pipelines for AI applications
• Monitor application performance and troubleshoot issues in production
• Design and maintain data pipelines, ETL/ELT workflows, and data infrastructure to support AI and analytics workloads

SKILLS

Must have

• Minimum of 6 to 9 years of experience in AI/ML solution implementation
• Minimum of 3 years of experience in Data Engineering (data pipelines, ETL/ELT, data warehousing, batch/streaming processing)
• AI & ML Skills: Multi-Agent System Design & Orchestration Full-stack AI Integration (Frontend to Backend) Multi-Cloud AI Infrastructure (AWS Bedrock, Vertex AI, Azure AI, Snowflake Cortex) Advanced Prompt Engineering & LLM Fine-tuning Agentic Retrieval Augmented Generation (RAG) AI Safety, Guardrails & Governance Enterprise Application Integration & AI Orchestration Semantic Modeling & Knowledge Graph Construction High-Scale Vector Database Management LLM Observability, Evaluation & Monitoring (LLMOps)
• Data Engineering Skills: Data pipeline design & orchestration (Apache Airflow, Prefect, Dagster) ETL/ELT development and optimization Data warehousing & lake architecture (Snowflake, BigQuery, Redshift, Databricks) Batch and streaming data processing (Spark, Kafka, Flink) Data modeling and schema design SQL proficiency and query optimization
• Main Technologies: Python (FastAPI / Pydantic) LangChain & LangGraph Edio & Render (Deployment & Hosting) Streamlit & Gradio (UI/UX for AI) OpenAI & Open-Source Models (Llama 3, Mistral) Vector Databases (Pinecone, Milvus, Weaviate) Cloud Platforms: AWS Bedrock, Google Vertex AI, Azure AI Studio LLM Monitoring Tools (LangSmith / Arize Phoenix) Data Tools: Apache Spark, Airflow, Kafka, dbt, Snowflake

Nice to have

Tesseract OCR