Software Engineer

Job Summary

The Software Engineer builds scalable full-stack software components while systematically evaluating the output, logic, and debugging capabilities of experimental AI models. Core responsibilities include writing clean, optimized code across Java, Python, and JavaScript, structuring relational database schemas, designing robust RESTful API integration layers, contributing to distributed system architecture strategies, and documenting technical insights for AI research teams.

Technical Spectrum & Domain Context

Engineers in this position operate across a highly versatile, polyglot technical spectrum designed to train AI models across different tech stacks:

• Backend Foundations: Writing object-oriented, enterprise-grade logic using Java (e.g., Spring Boot) and Python (e.g., FastAPI, Django).
• Frontend & Scripting Layers: Implementing clean, event-driven behaviors using JavaScript and modern web framework architectures.
• Data & Infrastructure Layers: Designing relational SQL schemas, constructing performant queries, and managing code delivery via automated Git workflows, comprehensive unit testing, and CI/CD pipelines deployed to cloud platforms (AWS, Azure, or GCP).

Experience & Competencies

Candidates must demonstrate deep full-stack programming agility, strong foundational knowledge of computer science principles, and excellent analytical skills:

Core Software Engineering Capabilities

• Professional Tenure: Minimum of 4+ years of verified professional experience operating as a full-time software engineer.
• Polyglot Fluidity: Advanced, hands-on production expertise across three core languages: Java, JavaScript, and Python.
• Computer Science Fundamentals: Deep, practical understanding of advanced algorithms, data structures, and Object-Oriented Programming (OOP) paradigms.
• Database & API Integration: Proficient in modeling, querying, and tuning SQL databases alongside a proven history of designing and integrating secure RESTful APIs across distributed environments.
• Modern Devops Practices: Robust experience navigating version control systems (Git), setting up continuous integration/continuous delivery (CI/CD) pipelines, writing strict unit tests, and operating inside Agile team workflows.

Preferred Qualifications

• Distributed Systems Architecture: Prior exposure to designing software architecture for high-concurrency microservices and distributed systems.
• Frontend Framework Literacy: Experience developing within modern frontend framework systems (e.g., React, Vue, or Angular).
• Technical Mentorship: Active participation in running code reviews, establishing team clean-code guidelines, and providing technical mentorship to peers.

Key Responsibilities

1. Full-Stack Software Engineering & Optimization (45%)

• Write Clean, Polyglot Code: Design, implement, and maintain scalable backend and frontend application layers using Java, JavaScript, and Python.
• Construct Secure APIs: Build, document, and deploy robust RESTful APIs, ensuring secure, high-efficiency data exchanges across distributed cloud systems.
• Manage SQL Architectures: Model complex database schemas, write optimized SQL queries, and perform routine database tuning to support high-performance applications.

2. AI Code-Generation Evaluation & Stress-Testing (35%)

• Audit Model Reasonings: Use your deep engineering knowledge to review, grade, and refine code generated by experimental AI models—identifying subtle logic errors, security vulnerabilities, or anti-patterns.
• Design Algorithmic Prompts: Craft complex software problems, edge cases, and architectural challenges to stress-test how effectively AI models can plan, write, and refactor code.
• Trace System Deficiencies: Troubleshoot and debug complex code failures, providing detailed documentation and feedback loops to explain exactly where an AI agent's logic broke down.

3. Architecture Design & Agile Collaboration (20%)

• Shape System Scalability: Participate in foundational system architecture discussions, advocating for cloud deployment best practices, high maintainability, and clean code principles.
• Engage in Agile Workflows: Collaborate actively within distributed Agile teams, turning high-level product requirements into clear, step-by-step technical blueprints.
• Refine Engineering Standards: Run peer code reviews, verify unit-test coverage thresholds, and maintain top-tier development hygiene across all internal and model-generated repositories.

Expected Outputs & Deliverables

• Optimized, highly maintainable production code units written in Java, Python, and JavaScript.
• Labeled, high-quality training inputs, edge-case evaluations, and code-diagnostic datasets for machine learning feedback loops.
• Scalable relational database models and secure API connection layers.
• Comprehensive technical issue reports, prompt logs, and structured evaluations outlining AI model performance and code safety metrics.

Skills Required:

• Computer / Software / It / Data