Senior Python Engineer – Multi-Agent AI (AWS, LangGraph)
About the Role
We are looking for a Senior Python Engineer to design and build enterprise-grade multi-agent AI systems on AWS. In this role, you will architect and develop intelligent agent solutions using LangGraph, LangChain, and AWS Bedrock AgentCore Runtime, focusing on scalable orchestration, stateful workflow execution, human-in-the-loop (HITL) processes, and distributed agent collaboration.
You will work closely with architects, platform engineers, and product teams to deliver production-ready AI solutions that are reliable, scalable, and aligned with enterprise engineering standards.
Project Overview
Our customer is a multinational corporation with more than a century of history and operations in over 180 countries. One of its key strategic initiatives is the development and adoption of a new generation of Reduced-Risk Products (RRPs), targeting more than one billion consumers worldwide.
Intellia partners with the customer to engineer a comprehensive software ecosystem supporting innovative IoT products, digital commerce, and enterprise platforms. The engineering organization develops core platform components powering best-in-class eCommerce, Digital Marketing, and IoT solutions.
As a Senior Python Engineer, you will join the Core Architecture Team, contributing to the design and implementation of a modern Digital Engineering Enterprise Platform.
The platform consists of services and applications that accelerate software delivery by providing engineering teams with reusable technologies, standardized development practices, compliance controls, and operational capabilities across more than 700 enterprise applications.
Responsibilities
- Design, develop, and maintain enterprise-grade multi-agent AI applications using Python, LangGraph, and LangChain.
- Build scalable agent workflows leveraging AWS Bedrock AgentCore Runtime.
- Implement advanced orchestration patterns, including supervisor/worker, fan-out/fan-in, and collaborative multi-agent architectures.
- Design stateful workflow execution using LangGraph checkpointing, recovery, and persistence mechanisms.
- Develop resilient, fault-tolerant, and idempotent execution strategies for long-running AI workflows.
- Integrate Human-in-the-Loop (HITL) approval processes into business-critical agent workflows.
- Enable agent delegation and collaboration through Agent Gateway and Agent-to-Agent (A2A) communication.
- Implement memory, context management, and persistence strategies for AI agents.
- Optimize workflow scalability, reliability, observability, and performance within distributed cloud environments.
- Collaborate with platform, security, DevOps, and product teams to deliver production-ready AI solutions.
- Define engineering standards, testing strategies, and operational best practices for agent-based applications.
- Support deployment, monitoring, troubleshooting, and continuous improvement of AI solutions running on AWS.
Requirements
- Bachelor's degree in computer science, Software Engineering, or a related field.
- 5+ years of professional Python software engineering experience.
- Hands-on experience building multi-step agent workflows with LangGraph.
- Strong experience with LangChain.
- Experience with AWS Bedrock AgentCore Runtime.
- Solid understanding of multi-agent orchestration patterns, including supervisor/worker and fan-out/fan-in architectures.
- Experience implementing LangGraph checkpointing and state management.
- Knowledge of Human-in-the-Loop (HITL) workflow design.
- Experience with Agent-to-Agent (A2A) delegation through Agent Gateway.
- Experience with workflow orchestration platforms such as Temporal, Apache Airflow, or similar.
- Strong understanding of distributed systems concepts, including checkpointing, idempotency, fault tolerance, and workflow recovery.
- Experience building scalable, cloud-native applications on AWS.
- Strong problem-solving, communication, and collaboration skills.
Nice to Have
- Experience evaluating AWS AgentCore Runtime maturity and enterprise adoption.
- Hands-on experience with AWS Bedrock Memory API.
- Experience integrating enterprise approval workflows into Human-in-the-Loop AI systems.
- Experience with AI observability, monitoring, and production operations.
- Familiarity with CI/CD pipelines and Infrastructure as Code in AWS environments.
Why Join Us
- Work on enterprise-scale AI initiatives for a global industry leader.
- Design and build next-generation multi-agent AI systems using cutting-edge AWS technologies.
- Influence architecture decisions and engineering best practices across large-scale platforms.
- Collaborate with highly experienced architecture and engineering teams on innovative cloud-native solutions.
- Opportunity to shape the future of enterprise AI orchestration in production environments.
