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# Lead Full Stack Engineer in Mundelein

- **Company:** Energy Jobline
- **Location:** Mundelein, IL, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Software Quality, Continuous Integration, DevOps, Django Web Framework, Elasticsearch, Graph Database, Monitoring of Systems, Python (Programming Language), NoSQL, Role-Based Access Control, Search Technologies, Service-Oriented Architecture, Software Engineering, TypeScript, Google Cloud, ReactJS, Retrieval-Augmented Generation, Indexer, AI Coding Agents, Backend, Fastapi, Vue.js, Event Driven Architecture, Webpack, AngularJS, Information Technology, Real Time Data, Apache Kafka, Build Tools, Graphql, Front End Software Development, Restful APIs, Stream Processing, Data Pipelines
- **Published:** October 31, 2026
- **Apply:** https://www.energyjobline.com/job/lead-full-stack-engineer-mundelein-32123230

## About the Role

* 5+ years of professional full stack software engineering, with demonstrated leadership in complex enterprise systems.
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 * Strong expertise in backend frameworks (FastAPI, Django) and frontend frameworks (React, Vue, Angular) with modern build tools (Vite).
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 * Proficiency in Python and TypeScript; solid understanding of data modeling (relational, NoSQL, graph databases).
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 * Extensive experience designing and consuming RESTful and GraphQL APIs, with large-scale, service-oriented architecture knowledge.
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 * Hands-on experience with event-driven systems (Kafka, cloud pub/sub) and asynchronous processing pipelines.
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 * Skilled in implementing security controls (RBAC, ABAC) and multi-tenant applications, with familiarity in search technologies (Elasticsearch, vector search).
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 * Deep understanding of cloud- development in AWS; CI/CD, observability, and automation practices.
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 * Familiarity with AI/ML feature integration, including retrieval-augmented (RAG), semantic search, and AI workflow observability., * Advanced degree in Computer Science, Software Engineering, or related fields; relevant cloud certifications (AWS, Azure, GCP).
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 * Experience in data-intensive industries such as finance, property management, or enterprise analytics.
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 * Active use of AI coding assistants and agents, with an understanding of their application in modern software development workflows.
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 * Knowledge of search optimization and domain-specific data modeling within complex enterprise environments.
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## Description

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 * Lead the design, development, and deployment of full stack applications, including backend services, APIs (REST/GraphQL), and frontend interfaces, ensuring modularity, security, and high performance.
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 * Collaborate with cross-functional teams-Product, Design, Data Science-to translate requirements into intuitive, reliable user experiences and scalable backend solutions.
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 * Define and evolve canonical data models, manage complex entity relationships (graphs, hierarchies), and develop indexing/search solutions (Elasticsearch, vector search) supporting AI-driven search and recommendation features.
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 * Build event-driven architectures (Kafka, cloud pub/sub), implementing asynchronous workflows and stream processing for scalable, real-time data handling.
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 * Integrate AI/ML functionalities-such as retrieval-augmented (RAG), semantic search, and entity resolution-into workflows, optimizing usability and business impact.
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 * Establish frontend architecture using modern frameworks (React, Vue, Angular) with focus on performance, accessibility, and shared UI component libraries.
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 * Drive service reliability, system observability, automated testing, and continuous improvement practices.
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 * Implement robust security measures, including role-based (RBAC) and attribute-based access controls (ABAC), across all layers of the application stack.
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 * Mentor engineering teams in architecture, code quality, and technical innovation, fostering best practices and engineering excellence.
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 * Coordinate with DevOps and Security to ensure compliant, scalable, and resilient infrastructure, primarily on cloud platforms like AWS.
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