Backend Software Engineer (Java / Spring)
Backend engineer builds and scales Java/Python microservices for an AI-powered commercial real estate platform, integrating LLMs and agent workflows on AWS.
- Compensation
- $120K–$180K / yr
- Location
- Europe
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Backend
- Posted
Skills
Full description
About Us
Smart Capital Center is an end-to-end, AI-powered platform for Commercial Real Estate (CRE) investment and financial management. We power real-time underwriting, asset management, and portfolio analytics through a combination of live data, workflow automation, and AI-driven insights.
Operating at the intersection of Generative AI, finance, and real estate, we are building systems that digitize and simplify complex financial workflows.
Our clients include leading institutions such as JLL, Pacific Life Insurance Company, and KeyBank. We are a lean, high-performance team building category-defining technology in a $17 trillion industry.
To learn more about our platform and vision, please visit our website.
The Role
We are looking for a Backend Software Engineer with strong experience in building scalable systems and a deep interest in AI-powered applications.
This is a high-impact, hands-on role where you will design and build backend services, integrate AI capabilities, and develop intelligent, agent-driven workflows used in real-world production environments.
You will work closely with product, AI, and engineering teams to deliver reliable, high-performance systems and automation features.
What You Will Do
Backend Development
Design, build, and maintain backend services using Java (Spring Boot) and Python
Develop scalable APIs and microservices for data-intensive applications
Optimize system performance, reliability, and scalability
Design efficient data models and handle complex integrations
AI & Intelligent Systems
Implement and integrate AI-powered features into core products
Design and build agent-based workflows for automation and decision-making
Apply prompt engineering techniques to improve LLM outputs and behavior
Work with modern AI frameworks to productionize intelligent systems
Cloud & Infrastructure
Develop and deploy backend systems on AWS (EC2, S3, RDS, Lambda, etc.)
Build resilient, scalable cloud-native services
Contribute to system monitoring, logging, and reliability
System Design & Engineering Excellence
Contribute to architecture, service boundaries, and system design decisions
Write clean, maintainable, and well-documented code
Ensure security, performance, and operational stability
Continuously improve engineering quality and development practices
Collaboration
Work closely with frontend, product, and AI teams