Associate Software Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an Associate Software Engineer based in the United States. We are seeking a motivated Associate Software Engineer to contribute to the development, testing, and continuous improvement of innovative software solutions in the healthcare technology sector. In this role, you will collaborate with experienced engineers and cross-functional teams to build reliable, scalable, and maintainable applications that support better healthcare outcomes. You will work with modern development practices and AI-assisted engineering tools to streamline workflows, improve code quality, and accelerate software delivery. The position also offers opportunities to explore data platforms, machine learning pipelines, and generative AI technologies while strengthening your technical expertise. You will contribute to architectural discussions, quality assurance, documentation, and reusable engineering practices within a collaborative and supportive environment. This is an excellent opportunity for an early-career engineer eager to grow professionally while making a meaningful impact through technology. \n Accountabilities:

Software Development:

Collaborate with engineering teams to design, develop, test, and maintain software applications. Write clean, efficient, secure, and maintainable code that follows established development standards and best practices. Feature Development and Enhancement:

Contribute to the implementation of new features, application improvements, and technical solutions aligned with business and project requirements. Code Reviews and Quality Assurance:

Participate in peer code reviews, identify potential improvements, and help ensure code quality, consistency, reliability, and compliance with engineering standards. Troubleshooting and Debugging:

Investigate software defects, diagnose technical issues, implement corrective solutions, and support ongoing application maintenance. Testing and Validation:

Develop and execute tests to validate application functionality, reliability, and performance, ensuring solutions meet defined quality requirements. Cross-Functional Collaboration:

Work closely with engineers and other 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 for review. AI Output Validation:

Assess AI-generated code and other technical outputs for correctness, security, maintainability, regulatory compliance, and alignment with business needs. Help review AI-assisted work produced by other engineers. Data Platform Development:

Contribute to the design and maintenance of data platforms and governed datasets that support analytics, machine learning, and generative AI applications. Reusable Engineering Practices:

Develop and share reusable prompts, AI agents, engineering playbooks, development workflows, and automation patterns that improve productivity across the engineering organization. Documentation and Continuous Improvement:

Maintain clear technical documentation, stay informed about emerging technologies, and recommend improvements to engineering tools, processes, and delivery practices. Responsible AI and Compliance:

Ensure that AI-assisted development activities follow organizational policies and applicable requirements for intellectual property, information security, privacy, protected health information (PHI), and responsible AI use. Requirements:

Education:

Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline. Programming Skills:

Proficiency in at least one programming language, such as C# or Python, with the ability to write readable, efficient, and maintainable code. 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 for managing code changes and collaborating with other developers. Agile Methodologies:

Understanding of software development methodologies such as Agile and Scrum, including collaborative planning, iterative delivery, and continuous improvement. Problem-Solving Skills:

Strong analytical thinking, attention to detail, and the ability to investigate technical issues and develop practical solutions. Communication and Collaboration:

Good written and verbal communication skills, with the ability to work effectively within a team, receive feedback, and contribute to shared engineering objectives. Adaptability and Learning:

Willingness to learn new technologies, explore emerging engineering practices, and continuously improve technical capabilities. AI-Assisted Development Experience:

Familiarity with AI-powered coding tools and a demonstrated ability to use them effectively in software development is preferred. Relevant platforms may include GitHub Copilot, Cursor, Claude Code, or similar solutions. Prompt Engineering and AI Delivery:

Strong prompt-writing skills and experience applying AI-assisted techniques to coding, testing, debugging, and other stages of software delivery are desirable. Data and AI Technologies:

Exposure to machine learning data pipelines, vector search, document processing, data preparation, or generative AI workloads is an advantage. Data Governance:

Working knowledge of data governance, data lineage, data quality, and observability practices supporting reliable AI-enabled solutions is preferred. Security and Responsible AI:

Understanding of secure software development, privacy protection, intellectual property safeguards, and responsible AI principles, particularly in environments handling sensitive healthcare information. Remote Work Readiness:

Ability to work remotely with a reliable high-speed internet connection exceeding 10 Mbps and the technical setup required to perform the role effectively. Benefits:

Comprehensive Benefits Package:

Access to a range of employee benefits, including health insurance, for eligible employees. Remote Work Environment:

Work-from-home flexibility designed to support productivity and work-life balance. Work-Life Balance:

A workplace culture that values employee wellbeing, flexibility, and autonomy. Professional Development:

Opportunities to expand technical skills, learn emerging technologies, and develop expertise in software engineering and AI-assisted development. 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 cross-functional colleagues in an environment that values inclusion, teamwork, and continuous learning. Meaningful Impact:

The opportunity to contribute to technology solutions that support healthcare organizations and help improve outcomes for people with complex medical needs. Inclusive Workplace:

A commitment to equal employment opportunities, accessibility, and respect for diverse backgrounds and perspectives. Compensation:

Salary details were not specified in the available job posting. Compensation is determined according to the position's requirements, the selected candidate's skills, and relevant professional experience. \n

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