> Markdown version of [/jobs/ext/4187868-python-full-stack-software-engineer-react](https://www.wearedevelopers.com/jobs/ext/4187868-python-full-stack-software-engineer-react). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Python Full-Stack Software Engineer -(React)

- **Company:** Manulife
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $86,100.0 - $136,100.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, User Authentication, Microsoft Azure, Big Data, Code Review, Computer Engineering, Data Validation, Information Engineering, Web Development, Github, Information Extraction, Python (Programming Language), MongoDB, OpenAI, Software Engineering, Web Application Frameworks, Enterprise Search, Azure Service Bus, Data Ingestion, Spring Cloud, LangChain, ReactJS, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Software Security, Generative AI, Backend, Agentic-AI, Fastapi, Data Layers, Containerization, AI Platforms, Kubernetes, Information Technology, AutoGen, Cosmos DB, Front End Software Development, Model Context Protocol, Intelligent Document Processing, Data Pipelines, Api Management, Databricks
- **Published:** October 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e795d976f5d67fcd

## About the Role

* 3+ years of professional software engineering experience, with strong backend and full-stack development expertise.
 * Hands-on development experience with Python, Java, and React.
 * Experience developing backend services and APIs using FastAPI, asynchronous Python frameworks, or similar technologies.
 * Practical experience building LLM-based or agentic AI solutions using LangGraph, LangChain, AutoGen, or comparable frameworks.
 * Hands-on experience developing RAG solutions, including embeddings, vector or hybrid search, and enterprise data sources.
 * Data engineering experience with Azure Databricks, data ingestion pipelines, Delta Tables, and large datasets.
 * Experience with cloud-native technologies such as AKS/Kubernetes, GitHub Actions, Azure API Management, Azure Service Bus, MongoDB/Cosmos DB, and vector databases.
 * Strong understanding of application security, including authentication, authorization, input validation, and data protection.
 * Strong verbal and written communication skills, with the ability to clearly explain technical approaches and trade-offs to both technical and business audiences.
 * A collaborative mindset combined with the ability to independently own and deliver work.

Nice to Have

 * Bachelor's or Master's degree in Computer Science, Computer Engineering, Software Engineering, Information Technology, or a related discipline.
 * Experience with Azure AI Search, Azure OpenAI, Azure AI Foundry, or comparable AI platforms.
 * Experience with intelligent document processing, including OCR, document extraction, classification, and data validation.
 * Working knowledge of Model Context Protocol (MCP), tool calling, and AI integration patterns.

## Description

* Design, develop, and maintain end-to-end applications across front-end, backend, API, AI, and data layers.
 * Build responsive and accessible user experiences using React and modern web development practices.
 * Develop scalable backend services and APIs using Python, FastAPI/async frameworks, and Java.
 * Build and integrate LLM-powered and agentic AI applications using frameworks such as LangGraph, LangChain, AutoGen, or similar technologies.
 * Design Retrieval-Augmented Generation (RAG) solutions using embeddings, vector/hybrid search, and enterprise knowledge sources.
 * Build and maintain data ingestion pipelines and work with large datasets using Azure Databricks and Delta Tables.
 * Develop cloud-native applications leveraging AKS/Kubernetes, Azure API Management, Azure Service Bus, MongoDB/Cosmos DB, and vector databases.
 * Establish and maintain automated build, integration, and deployment pipelines using GitHub Actions.
 * Implement strong engineering practices across testing, code reviews, observability, security, performance, and reliability.
 * Troubleshoot complex production issues, conduct root-cause analysis, and drive issues through resolution.
 * Partner with product, design, QA, engineering, and business stakeholders to translate requirements into effective technical solutions.
 * Contribute to architectural decisions and advocate for scalable, consistent engineering standards across the stack.
 * Take ownership of individual deliverables and drive work forward with minimal supervision.