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Location
Remote (Ukraine)
Employment
Full-Time

First seen by Alion on Oct 13, 2026.

Overview
Company
Impact
Profile match
Trusted by Leadership team with deep experience in technology and commercial real estate Contact Us Learn more about how we're redefining commercial real estate lending and investment 535 Mission Street, 14th floor San Francisco, CA, 94105 +1 (877) 721 - 4977 [email protected] Trusted by…

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
Contribute to end-to-end feature delivery
Participate in Agile development processes
Requirements
5+ years of backend software development experience
Strong experience building and scaling backend systems in production
Core Technical Skills
Strong experience with Java and Spring Boot
Solid experience with Python
Strong knowledge of SQL and database design (PostgreSQL preferred)
Experience building REST APIs, microservices, and distributed systems
Hands-on experience with AWS (EC2, S3, RDS, Lambda, etc.)
Proficiency with Git and modern development workflows
AI & Modern Development Experience
Experience with prompt engineering for LLM-based systems
Practical experience building AI agent workflows in production
Familiarity with frameworks/tools such as:LangGraph
LangChain
LangSmith
or similar ecosystems

Experience using AI-assisted development tools, such as:Claude Code
Codex
OpenCode
or similar

Nice to Have
Experience with vector databases or semantic search (e.g., Milvus)
Knowledge of RAG (Retrieval-Augmented Generation) architectures
Experience with CI/CD pipelines and DevOps practices
Familiarity with event-driven architecture
Experience with data processing pipelines or document AI systems

Why Join Us
Work on cutting-edge AI-powered systems in a $17T industry
Build real-world applications using LLMs, agents, and automation
High ownership and autonomy with meaningful technical impact
Opportunity to influence system design and engineering direction
Fast-moving, execution-focused team with minimal bureaucracy
Competitive compensation and flexible work environment

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