Associate Software Engineer

About the Role

Seeking a motivated Associate Software Engineer to contribute to the development, testing, and continuous improvement of innovative software solutions in the healthcare technology sector. This role involves collaboration with experienced engineers and cross-functional teams to build reliable, scalable, and maintainable applications. Opportunities exist to explore data platforms, machine learning pipelines, and generative AI technologies.

Key Responsibilities

• Software Development: Collaborate with engineering teams to design, develop, test, and maintain software applications. Write clean, efficient, secure, and maintainable code following established development standards.
• Feature Development and Enhancement: Contribute to implementing new features, application improvements, and technical solutions aligned with business and project requirements.
• Code Reviews and Quality Assurance: Participate in peer code reviews, identify improvements, and ensure code quality, consistency, reliability, and compliance with engineering standards.
• Troubleshooting and Debugging: Investigate software defects, diagnose technical issues, implement corrective solutions, and support application maintenance.
• Testing and Validation: Develop and execute tests to validate application functionality, reliability, and performance, ensuring solutions meet quality requirements.
• Cross-Functional Collaboration: Work closely with engineers and stakeholders to understand requirements, clarify technical specifications, and deliver effective software solutions.
• AI-Assisted Engineering: Apply AI-powered development tools throughout the software delivery lifecycle, including requirements analysis, coding, testing, debugging, documentation, and operational monitoring.
• Architecture and Solution Design: Use AI-assisted workflows to explore design alternatives, evaluate architectural approaches, improve existing systems, and prepare technical design artifacts.
• AI Output Validation: Assess AI-generated code and technical outputs for correctness, security, maintainability, regulatory compliance, and alignment with business needs. Review AI-assisted work from other engineers.
• Data Platform Development: Contribute to the design and maintenance of data platforms and governed datasets supporting analytics, machine learning, and generative AI applications.
• Reusable Engineering Practices: Develop and share reusable prompts, AI agents, engineering playbooks, development workflows, and automation patterns.
• Documentation and Continuous Improvement: Maintain technical documentation, stay informed about emerging technologies, and recommend improvements to engineering tools, processes, and delivery practices.
• Responsible AI and Compliance: Ensure AI-assisted development activities adhere to organizational policies and applicable requirements for intellectual property, information security, privacy, protected health information (PHI), and responsible AI use.

Requirements & Tech Stack

• Programming Skills: Proficiency in at least one programming language, such as C# or Python.
• Software Development Fundamentals: Basic understanding of software engineering principles, application development lifecycles, testing methodologies, debugging techniques, and coding best practices.
• Version Control: Familiarity with Git or comparable version control systems.
• Agile Methodologies: Understanding of Agile and Scrum.
• Problem-Solving Skills: Strong analytical thinking and attention to detail.
• Communication and Collaboration: Good written and verbal communication skills.
• Adaptability and Learning: Willingness to learn new technologies and improve technical capabilities.
• Remote Work Readiness: Ability to work remotely with a reliable high-speed internet connection (exceeding 10 Mbps).

Qualifications

• Education: Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.
• AI-Assisted Development Experience (Preferred): Familiarity with AI-powered coding tools and ability to use them effectively. Relevant platforms may include GitHub Copilot, Cursor, Claude Code, or similar solutions.
• Prompt Engineering and AI Delivery (Desirable): Strong prompt-writing skills and experience applying AI-assisted techniques to coding, testing, debugging, and other stages of software delivery.
• Data and AI Technologies (Advantageous): Exposure to machine learning data pipelines, vector search, document processing, data preparation, or generative AI workloads.
• Data Governance (Preferred): Working knowledge of data governance, data lineage, data quality, and observability practices.
• Security and Responsible AI (Preferred): Understanding of secure software development, privacy protection, intellectual property safeguards, and responsible AI principles, particularly in sensitive healthcare environments.

Benefits

• Comprehensive Benefits Package: Access to employee benefits, including health insurance (for eligible employees).
• Remote Work Environment: Work-from-home flexibility.
• Work-Life Balance: Workplace culture valuing employee wellbeing, flexibility, and autonomy.
• Professional Development: Opportunities to expand technical skills and learn emerging technologies.
• Innovative Technology Exposure: Hands-on experience with AI-powered engineering tools, machine learning data platforms, and generative AI development practices.
• Collaborative Culture: Opportunities to work alongside engineers and colleagues in an inclusive environment.
• Meaningful Impact: Opportunity to contribute to technology solutions supporting healthcare organizations.