Ai Engineer

AI Engineer at Built In — Research Report

Introduction

The AI Engineer role at Built In offers a unique pathway for tech professionals to shape the future of artificial intelligence while working with a company that defines industry standards. This position is ideal for candidates eager to build real AI systems, from agents to automation workflows, in a remote or hybrid environment across the US. While the specific deadline is not mentioned, securing this role early provides significant career advantages, including access to cutting-edge projects and potential full-time conversion opportunities.

Overview of Built In

Built In is a premier platform connecting top talent with innovative companies, specifically focusing on tech hubs like San Francisco, Boston, and New York. The company operates as a niche marketplace for software engineering, data science, and AI roles, distinguishing itself from general job boards by offering deep insights into company culture and growth trajectories. Its key products include localized job portals, company reviews, and exclusive content that helps job seekers understand the "inside" of tech companies.

In the industry, Built In competes with platforms like LinkedIn and Glassdoor but maintains a stronger niche by focusing exclusively on the tech ecosystem. The company has seen steady growth, expanding its reach to multiple major US cities and becoming a trusted resource for both employers and candidates. Its reputation is built on transparency, providing honest reviews and detailed data that help users make informed career decisions.

People want to work at Built In because it offers a dynamic work environment where they can directly impact how tech talent is discovered and hired. The culture is collaborative, innovative, and driven by a mission to democratize access to top tech jobs. Employees often cite the opportunity to work with high-profile tech companies and the fast-paced nature of the platform as key reasons for their enthusiasm.

AI Engineer Role

Role Overview

An AI Engineer at Built In is responsible for designing, building, and iterating on advanced AI systems that enhance the platform's functionality and user experience. Day-to-day, the intern or employee works on projects involving AI agents, agentic operating systems, and local large language models. The role has a direct impact on the product by enabling smarter search algorithms, automated content generation, and more intuitive user interactions.

Detailed Responsibilities

• Design and build software APIs that enable internal and external access to AI systems
• Build tools to automate and maintain computing clusters and data parsing pipelines
• Research, prototype, test, and build real AI systems for automation workflows
• Collaborate with cross-functional teams to support the design and development of AI features
• Develop agent-based systems to automate developer and user workflows

Day-to-Day Workflow

A typical day starts with reviewing the status of ongoing AI projects and coordinating with the engineering team via remote communication tools. The engineer then spends several hours coding, testing, and refining AI models, often focusing on LLM integration or agent behavior. Mid-day involves a team sync to discuss progress, troubleshoot issues, and align on next steps. The afternoon is dedicated to deep work on specific tasks, such as building data pipelines or optimizing model performance, followed by documentation and code commits.

Tools and Technologies

The tech stack includes Python for core development, along with frameworks like LangChain for building AI agents and Hugging Face for model management. Engineers use local large language models and APIs from major providers to power automation workflows. Data infrastructure relies on tools for managing computing clusters, while version control is handled through Git. Collaboration platforms like Slack and Jira are essential for team coordination and project tracking.

Skills and Requirements

Technical Skills

Candidates must possess strong proficiency in Python and experience with LLMs, whether through APIs, local models, or personal projects. Knowledge of AI agents, agentic operating systems, and automation workflows is critical. Familiarity with data parsing pipelines, computing cluster management, and API development is also required. A solid understanding of machine learning fundamentals and software architecture is essential for success.

Soft Skills

Effective communication is vital for collaborating with cross-functional teams and explaining complex AI concepts to non-technical stakeholders. Teamwork skills are necessary to thrive in a collaborative environment, while problem-solving abilities help tackle the unique challenges of AI development. Curiosity and initiative are highly valued, as the role often requires exploring new technologies and proposing innovative solutions.

Experience Expectations

Built In targets motivated candidates with relevant experience, such as internships, personal projects, or academic work in AI. A portfolio showcasing GitHub repos, demos, apps, chatbots, or project write-ups is strongly preferred. While a graduate degree is not required, candidates should demonstrate a clear passion for AI and the ability to build real systems. GPA expectations are flexible, with a focus on practical skills and project quality over academic metrics.

Salary and Benefits

The estimated pay range for an AI Engineer internship at Built In is $20–$35 per hour, depending on experience and location. Full-time roles typically offer competitive salaries aligned with market standards for AI engineers in the US tech sector. Perks include a remote or hybrid work environment, flexible hours, and a learning budget for courses and certifications. The internship may also offer stipends for exceptional candidates and opportunities for full-time conversion after completion.

Built In Hiring Process

Step-by-Step Hiring Stages

1. Application: Submit resume and project links via the company portal or Handshake
2. Screening: ATS review for keywords and portfolio quality
3. Assignment: Complete a technical task or AI prototype challenge
4. Interviews: Participate in technical and behavioral interviews with the team
5. Offer: Receive a formal offer with details on compensation and start date

Application Timeline

Candidates should apply as soon as the role is posted, as deadlines are not always fixed. The typical process duration ranges from two to four weeks, depending on the volume of applicants and the complexity of the assignment. Early application is recommended to secure a spot in the review queue and avoid last-minute competition.

Screening Methods

The screening process relies on an ATS that scans for keywords like "AI agents," "LLMs," and "automation workflows." A strong portfolio with project links is critical, as applications including GitHub repos or demos receive the strongest consideration. Recruiters also evaluate the quality of the project write-up and the candidate's ability to articulate their excitement for AI innovation.

Interview Preparation

Example Interview Questions

• What are you most excited to build, test, or explore in AI right now?
• How would you design an AI agent to automate a specific developer workflow?
• Describe your experience with local large language models and how you integrated them into a project.
• What challenges have you faced when building data parsing pipelines for AI systems?

How to Answer

Use the STAR method (Situation, Task, Action, Result) to structure responses, providing concrete examples of past projects. Focus on demonstrating technical depth while explaining the impact of your work. For questions about excitement in AI, highlight specific trends like agentic systems or local LLMs and explain why they matter. Always tie your answers back to how your skills can benefit Built In's mission.

What Recruiters Evaluate

Recruiters evaluate technical proficiency, problem-solving abilities, and the quality of the candidate's portfolio. They look for curiosity, initiative, and the ability to collaborate effectively in a remote environment. Communication skills are also critical, as the role requires explaining complex AI concepts to diverse stakeholders. A strong alignment with Built In's values and mission is a key factor in the final decision.

How to Get Selected

Practical Tips

• Submit a resume with clear keywords like "AI agents" and "LLMs" to pass ATS screening
• Include a link to a high-quality GitHub repo or demo that showcases your AI skills
• Write a concise note answering what you are excited to build in AI, highlighting specific trends
• Tailor your application to Built In's focus on tech hubs and innovation
• Network with current employees or recruiters to gain insider insights

Common Mistakes to Avoid

• Submitting an application without a project link, which significantly reduces consideration
• Using generic language that fails to demonstrate passion for AI innovation
• Overlooking the importance of soft skills like communication and teamwork
• Applying too late, missing the window for early review
• Failing to tailor the application to the specific role and company culture

How to Stand Out

To stand out, build a portfolio with diverse AI projects, such as chatbots, automation tools, or agent-based systems. Network with Built In employees through LinkedIn or industry events to show genuine interest. Tailor your submission to highlight how your skills align with the company's mission of connecting talent with tech innovation. A well-written project description that explains the "why" behind your work can make a significant difference.

Final Thoughts

The AI Engineer role at Built In is a gateway to shaping the future of artificial intelligence while working with a company that leads the tech industry. With competitive pay, flexible work options, and the chance to build real AI systems, this opportunity is perfect for motivated candidates ready to make an impact. Take action now by preparing your portfolio, tailoring your application, and applying early to secure your spot in this exciting role.

Frequently Asked Questions

Q: What is the salary for an AI Engineer at Built In? A: The internship salary is $20–$35 per hour, while full-time roles offer competitive market-aligned salaries.

Q: How competitive is it to get hired at Built In? A: The process is moderately competitive, with a strong focus on portfolio quality and relevant AI experience.

Q: What skills are most important for this role? A: Proficiency in Python, experience with LLMs and AI agents, and the ability to build automation workflows are critical.