Full-Stack Engineer

As a Full-Stack Engineer at LMI, your main responsibilities will include architecting and refining backend systems, crafting and deploying robust Python code, and ensuring code quality through diligent testing. You'll also be engaging with stakeholders to discuss software challenges, collaborate with the development team for improved workflows, and document your code meticulously.

To qualify for the Full-Stack Engineer position at LMI, you should have 5-10 years of related experience and a Bachelor’s degree in Computer Science or a related field. At least 2 years of experience in Python development, Object Oriented Programming (OOP), and familiarity with enterprise-level software applications are necessary. Excellent communication skills and an active Secret clearance are also required.

A Full-Stack Engineer at LMI primarily needs to be proficient in Python and familiar with web frameworks. Knowledge of additional programming languages like JavaScript, along with tools such as Node.js and Postgres, is beneficial. Understanding of software development processes and best practices will also help you succeed in this position.

Collaboration is integral to the Full-Stack Engineer role at LMI. You'll be working closely with your software development team using GitLab to enhance workflows and drive initiatives. Regular meetings with internal managers and external customers will be part of your routine to ensure that challenges are promptly addressed and innovative solutions are co-created.

At LMI, Full-Stack Engineers are presented with numerous opportunities for growth. By engaging in advanced technologies and participating in innovative projects like the LIGER™ platform, you can enhance your technical skills while also gaining insights into generative AI applications. The collaborative environment fosters professional development, paving the way for possible advancement to senior roles or specialization in emerging technologies.

When answering this question, highlight your hands-on experience with Python development and specific web frameworks you've used. Discuss projects where you successfully implemented Python for backend solutions, focusing on your contributions and the challenges you overcame.

Mention your commitment to conducting thorough unit tests and using best practices for code reviews. Describe any guidelines you follow for documentation, testing methodologies, and how you incorporate feedback from peers to improve code quality.

Use this question to illustrate your teamwork skills. Detail the challenge, your role within the team, the strategies employed to tackle the issue, and the ultimate outcome, emphasizing how collaboration led to success.

Share your experiences in managing time effectively and adapting to varying tasks whether working independently or with a team. Provide specific examples that demonstrate your ability to navigate a dynamic environment without losing sight of project goals.

Discuss your commitment to professional development by mentioning resources you follow, such as tech blogs, online courses, or community meetups. Highlight any recent technologies you've explored or integrated into your work to show your proactive approach.

Talk about techniques you employ for understanding stakeholder needs, such as active listening and regular updates. Illustrate how these strategies have led to fruitful collaborations and successful project outcomes.

Explain your experience with version control using Git and how you've applied Agile principles in your past projects. Discuss the benefits you've seen, such as enhanced collaboration and quicker response times to changes.

Provide examples of your understanding of OOP principles such as inheritance, encapsulation, and polymorphism. Describe how you’ve applied these principles in projects, particularly in Python, to create maintainable and scalable code.

Share your perspective on the importance of documentation in ensuring code clarity for both current and future developers. Mention any tools or practices you utilize to maintain thorough and easily navigable documentation.

If applicable, describe the machine learning projects you’ve worked on, outlining the integration process, the technologies used, and the impact it had on application performance or user experience.