Agentic AI Engineer [Python / LangChain / LangGraph]

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)

Advanced Prompt Engineering & LLM Fine-tuning

Agentic Retrieval Augmented Generation (RAG)

AI Safety, Guardrails & Governance

Semantic Modeling & Knowledge Graph Construction

LLM Observability, Evaluation & Monitoring (LLMOps)

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

Streamlit & Gradio (UI/UX for AI)

LLM Monitoring Tools (LangSmith / Arize Phoenix)

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