Python AI Engineer

Client

Our client is a global asset, investment, and financial product management company operating across the United States and over 40 other countries.

As an AI Software Engineer, you will design, develop, and optimize advanced AI applications leveraging AWS Bedrock services and cutting-edge architectures. Your role will focus on building intelligent systems for extracting insights from financial and unstructured data, developing scalable APIs, and implementing modern approaches such as GraphRAG for knowledge retrieval. You will ensure robust backend performance with FastAPI, maintain comprehensive test coverage, and drive efficiency in production environments by optimizing model performance, cost, and latency.

Responsibilities

• Design and implement AI-driven applications using AWS Bedrock services.
• Develop intelligent solutions for processing financial documents and unstructured data.
• Build high-performance backend services with Python and FastAPI, ensuring strong test coverage.
• Implement GraphRAG architectures to improve reasoning and knowledge retrieval.
• Create scalable API endpoints for model serving and conversational interfaces via Converse API.
• Optimize performance, cost, and latency of deployed models in production.
• Integrate workflows with multi-agent AI systems (e.g., LlamaIndex, LangChain, LangGraph, LangFlow, Strands Agents).
• Develop automated test pipelines with unit, integration, and load testing coverage.
• Implement evaluation frameworks for AI systems, ensuring quality and efficiency.
• Work with knowledge graphs and vector databases (e.g., OpenSearch, Neptune Analytics) for enterprise applications.

Requirements

• 4+ years of experience in AI/ML services and backend development with Python.
• Strong expertise in FastAPI and RESTful API design.
• Hands-on experience with multi-agent AI workflows (LlamaIndex, LangChain, LangGraph, LangFlow, Strands Agents).
• Proficiency in Python testing frameworks (unittest, pytest, testcontainers) and load testing (Locust).
• Experience building and deploying Converse API interfaces.
• Proven knowledge of RAG and GraphRAG architectures.
• Strong proficiency with AWS Bedrock services for model deployment and integration.
• Experience with knowledge graphs and vector databases (OpenSearch, Neptune Analytics).
• Ability to design integration tests with TestContainers for database and service dependencies.
• Practical experience with automation pipelines and coverage metrics.
• Understanding of token optimization and cost management in AI services.

Nice to have

• Experience with FastMCP for high-performance APIs.
• Background in applying AI solutions in financial services or regulated industries.
• Familiarity with hybrid systems combining rule-based approaches and AI models.
• Experience with multi-modal AI models and asynchronous Python patterns.
• Strong skills in API optimization and performance tuning.
• Knowledge of API gateway architectures and microservices.
• Bachelor’s degree in Finance, Economics, Statistics, Computer Science, or related field.