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

Mandatory Skills Description:

• • 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