Full Stack Software Engineer at JLL designing and developing applications integral to AI systems. Leading projects on scalable architectures using modern technologies.
Responsibilities
Design, implement, and support RESTful APIs, backend services, and microservices architectures using Python and Node.js.
Develop full stack solutions incorporating frontend (JavaScript frameworks) and backend components for scalable enterprise applications.
Build, optimize, and maintain search and retrieval systems, including integration with vector databases and information retrieval technologies.
Collaborate with data engineers to integrate AI/ML models and RAG systems into production.
Implement prompt engineering and optimization strategies to improve intelligent assistant interactions and AI-powered applications.
Lead maintenance, bug fixing, troubleshooting, and enhancements of existing codebases, ensuring reliability and performance.
Apply robust error handling, automated logging, and monitoring best practices for mission-critical cloud software.
Contribute to CI/CD pipeline automation, testing strategy, and quality assurance using Git, GitHub Actions, and Azure DevOps.
Support architectural discussions, code reviews, and technical decision-making processes for engineering excellence.
Translate business and functional requirements into technical deliverables in collaboration with cross-functional teams.
Stay current with emerging technologies and best practices in AI/ML, full stack development, cloud infrastructure, and search optimization.
Author and contribute to technical documentation, runbooks, and knowledge sharing initiatives.
Requirements
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related discipline.
At least 7 years of relevant experience in full stack software engineering; designing and delivering production applications.
Hands-on experience with Python and Node.js in enterprise environments.
Competency in modern frontend frameworks (React, Angular, or equivalent).
Solid experience building APIs, microservices, and distributed systems in Azure or other major cloud platforms (AWS, GCP).
Experience with vector databases, information retrieval systems, and optimizing search performance (highly preferred).
Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code in cloud settings.
Proficient in CI/CD, version control (GitHub/Git), and automated testing frameworks.
Experience with database technologies including SQL Server, CosmosDB, and both relational and NoSQL data modeling.
Exposure to prompt engineering, LLM integration, or AI tools is an advantage; RAG project experience strongly preferred.
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