Python / AI Engineer – Multi-Agent Systems
About the Role
We are looking for a Python / AI Engineer to design, build, test, and optimize intelligent multi-agent systems running on AWS Bedrock.
In this role, you will work at the intersection of Python engineering, generative AI, agent orchestration, and cloud-native architecture. You will help build production-grade AI applications using modern agent frameworks, implement multi-agent delegation patterns, establish evaluation and testing practices, and create reusable engineering patterns for AI development teams.
The ideal candidate combines strong Python engineering fundamentals with hands-on experience building AI agents and a passion for developing scalable, reliable, and maintainable AI solutions.
Project Overview
Our customer is a multinational corporation with more than a century of history and operations in over 180 countries, serving more than 1 billion consumers worldwide. The company is undertaking an ambitious transformation to introduce a new generation of Reduced-Risk Products (RRPs) and innovative consumer experiences.
With an IT landscape spanning 700+ applications, our teams are helping engineer a comprehensive software ecosystem supporting cutting-edge IoT, eCommerce, and Digital Marketing solutions.
As part of the Core Architecture Team, you will contribute to the architecture and implementation of best practices across the client's Digital Engineering Enterprise Platform.
The platform provides engineering teams with reusable services, technologies, tools, and practices that accelerate software development and delivery while addressing common SDLC, operational, compliance, governance, and engineering challenges.
What You'll Do
- Design and develop intelligent AI agent applications using Python and modern agent frameworks such as LangGraph, Strands, CrewAI, or equivalent.
- Design and implement multi-agent collaboration, orchestration, and delegation patterns for complex AI workflows.
- Integrate AI agents with AWS Bedrock foundation models and related AWS AI services.
- Build agent-to-agent (A2A) communication workflows using JSON-RPC 2.0, Server-Sent Events (SSE), and A2A wire formats.
- Develop robust testing strategies for agent behavior, workflow correctness, reliability, and regression prevention.
- Build automated evaluation workflows using tools such as pytest and LangSmith.
- Establish approaches for tracing, evaluating, and improving agent performance.
- Design reusable agent components, templates, reference implementations, and pattern libraries for engineering teams.
- Create high-quality technical documentation, implementation guides, architecture patterns, and best-practice documentation.
- Collaborate with AI, platform, architecture, and engineering teams to improve the performance, reliability, scalability, and maintainability of AI applications.
- Monitor, troubleshoot, and optimize agent workflows in production environments.
- Contribute to best practices for AI observability, testing, governance, security, and lifecycle management.
- Help define and promote engineering standards for production-grade generative AI and multi-agent applications.
What You'll Bring
Technical Skills
- Strong Python development skills.
- Hands-on experience with modern AI agent frameworks, such as:
- LangGraph
- Strands
- CrewAI
- or equivalent agent orchestration frameworks.
- Practical experience implementing multi-agent systems and delegation patterns.
- Experience integrating foundation models through AWS Bedrock APIs.
- Understanding of agent-to-agent (A2A) communication and delegation.
- Knowledge of JSON-RPC 2.0 and Server-Sent Events (SSE).
- Experience with automated testing and evaluation of AI/agent workflows.
- Familiarity with pytest and AI evaluation or observability tooling.
- Ability to create clear technical documentation and reusable engineering patterns.
Experience
- 4+ years of professional Python development experience.
- Hands-on experience building applications with AI agents or agentic workflows.
- Experience working with AWS Bedrock or comparable managed foundation-model platforms.
- Experience with at least one modern agent framework, such as LangGraph, Strands, CrewAI, or equivalent.
- Experience designing or implementing multi-agent delegation and orchestration workflows.
- Experience building automated tests for complex software workflows.
Nice to Have
- Hands-on experience with the Strands SDK.
- Experience with LangSmith tracing and evaluation.
- Experience with agent observability and production monitoring.
- Experience designing reusable AI engineering patterns or internal developer platforms.
- Familiarity with cloud-native architecture and AWS services.
- Experience working in enterprise-scale engineering environments.
Education
- Bachelor's degree in computer science, Software Engineering, Information Technology, or a related field.
Why Join Us
- Work on cutting-edge generative AI and multi-agent technology at enterprise scale.
- Build AI solutions using AWS Bedrock and modern agent frameworks.
- Solve complex engineering challenges involving orchestration, delegation, evaluation, and production reliability.
- Contribute to reusable AI architecture patterns and engineering standards adopted across development teams.
- Collaborate with experienced AI, architecture, platform, and software engineering teams.
- Gain exposure to a large-scale digital transformation supporting innovative IoT and consumer experiences.
- Play a key role in shaping how production-grade AI applications are designed, tested, deployed, and operated.
