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)
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- • 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 Skills Description:
- Tesseract OCR