Senior Software Engineer - Agent AI

As a Senior Software Engineer - Agent AI at Andesite, you'll have a variety of responsibilities. Your primary focus will involve designing, developing, and deploying agentic AI architectures using LLMs and RAG, working hard to ensure models meet specific use-case requirements. You will oversee the AI/ML infrastructure, manage the deployment lifecycles, and work on building scalable systems for monitoring and optimizing machine learning models. Collaboration is key in this role, and you will work across functional teams to bridge the technology with business insights, all while keeping pace with the latest advancements in AI and cybersecurity.

To qualify for the Senior Software Engineer - Agent AI position at Andesite, you should possess either a Master's or Ph.D. degree in computer science, statistics, mathematics or a related field, or have equivalent job experience. Additionally, you should have a minimum of five years of experience in software engineering, particularly in building scalable AI/ML solutions. Proficiency in programming languages like Python, R, or Scala is essential, alongside experience with machine learning frameworks like TensorFlow or PyTorch. Familiarity with cloud platforms such as AWS or Azure would be a great asset.

At Andesite, as a Senior Software Engineer - Agent AI, you can expect a flexible and supportive work environment. The company operates on a remote-first basis, which means you will have the opportunity to manage your work schedule to fit your lifestyle. The culture is built on collaboration, innovation, and inclusivity, fostering a strong sense of teamwork among professionals from diverse backgrounds. You can also anticipate occasional travel for in-person collaboration with your team and clients, enhancing your overall work experience.

In the role of Senior Software Engineer - Agent AI at Andesite, you'll be working with a broad range of technologies. This includes large language models (LLMs), retrieval-augmented generation (RAG), and various AI/ML frameworks like TensorFlow and PyTorch. You'll also engage with cloud services such as AWS, Azure, or GCP to build scalable and reliable infrastructure. Understanding cybersecurity concepts like threat detection and data encryption will also be essential, allowing you to integrate these security measures effectively into your projects.

As a Senior Software Engineer - Agent AI at Andesite, you'll be entitled to an attractive benefits package including a competitive salary ranging from $150,000 to $180,000 based on your experience and skills. Additionally, all employees receive comprehensive health insurance that covers medical, dental, and vision care for themselves and their families. You’ll also enjoy unlimited paid time off with manager approval, a flexible work environment, and 14 weeks of fully paid parental leave, making it a great place to work and grow your career.

In responding to this question, focus on specific projects you've worked on that involved AI and machine learning. Discuss how you approached design, development, and deployment, and the impact these products had on your organization. Mention any particular programming languages or frameworks you utilized, demonstrating your technical proficiency directly related to the Senior Software Engineer - Agent AI position at Andesite.

When answering this, articulate your process for validating and monitoring model performance. Discuss the metrics you track and the tools you use for observability. Highlight the importance of data quality and describe any practices you've implemented to enhance data collection and validation to ensure optimal performance in previous projects.

Use the STAR technique (Situation, Task, Action, Result) to structure your response. Share an example where collaboration with product managers or data scientists led to a successful machine learning solution. Emphasize your ability to communicate technical concepts clearly to non-technical stakeholders and how your teamwork contributed to meeting project goals.

In your response, detail your familiarity with cloud platforms such as AWS, Azure, or GCP. Provide specifics on how you've utilized these platforms for machine learning model deployment and infrastructure management. Mention any successful projects that benefited from cloud technologies, highlighting your ability to leverage them in scaling AI products.

Discuss the specific resources or strategies you use to stay informed about recent AI/ML developments. You might mention following leading researchers, engaging with online courses or attending conferences. Illustrate how this ongoing education has allowed you to implement innovative techniques in your work, tying it to the expectations for the Senior Software Engineer - Agent AI role.

Be specific about the languages you excel in, such as Python, R, or Scala. Discuss the projects you've completed using machine learning frameworks like TensorFlow or PyTorch, including your role in implementation and optimization. This showcases your direct application of the skills required for the Senior Software Engineer - Agent AI position.

Identify a challenge related to AI or machine learning development, such as dataset issues or model training difficulties. Describe how you addressed this challenge, the skills and knowledge you used, and the ultimate outcome. This also reflects your problem-solving capabilities, which are essential for the role at Andesite.

Explain the methodologies you apply for fine-tuning models, including any algorithms or automated processes you prefer. Discuss the importance of achieving accuracy and performance, relating this to your previous experiences. This can highlight your technical expertise which aligns well with the expectations for the Senior Software Engineer - Agent AI role.

Prepare to articulate your motivation for joining Andesite. Connect your career aspirations with their mission to redefine cybersecurity through AI collaboration. Mention any exciting aspects of their work culture or technical direction that resonates with you. This shows a tailored interest that aligns with their values and goals.

Convey how you prioritize data privacy in your AI/ML projects. Discuss any relevant practices you follow, such as data anonymization or compliance with regulations, and how they impact model development. This emphasizes your awareness of ethical considerations in technology, vital for a role involving cybersecurity.