AI Labs Engineer
Remote (ET & CT time zones only — some travel required)

About Clasp

Clasp is a venture-backed, mission-driven startup expanding access to education and career opportunities. We help employers attract and retain critical talent while giving colleges and universities new ways to support their students through education financing. At our core, we’re building tools for economic mobility.

Named to the Forbes Fintech 50, backed by SHRM, and recognized as Startup of the Year by StartUp Boston, Clasp operates across two business lines:

1. Clasp Talent helps healthcare employers attract and retain talent by connecting them with diverse candidates and using student loan repayment as a powerful recruiting and retention benefit.
   

2. Clasp Student Finance gives colleges and universities the technology to launch and operate their own private student loan programs, helping schools support students as the financial-aid landscape changes.
   
   

Why This Role

AI Labs exists to make AI useful in the day-to-day work of Claspmates. Over the past year, we’ve built internal products and workflows, helped teams develop practical AI skills, and created shared systems they can reuse. Today, over 70% of Claspmates use an agent/tool AI Labs built every week—and we’re ready to build on that momentum.

We’re hiring an early-career engineer as the second person in AI Labs to help shape what comes next. You’ll work across the full product loop: understand a workflow, identify the right problem, build across the stack, launch, see how people use what you built, and improve it.

This is an L1 role where you’ll get autonomy, feedback, and support while learning to own meaningful problems from beginning to end. You won’t spend your time implementing perfectly specified solutions, you’ll help figure out what should be built and why.

What you’ll do

• Own problems from discovery through adoption. Work directly with internal users to understand their workflows, build and launch solutions across the stack, and measure whether they helped.

• Build and improve internal tools. Refine existing agents and create new ones, including their instructions, tools, guardrails, evaluations, and human handoffs.

• Make your work maintainable. Document decisions, setup, risks, and operating steps. Raise architecture, security, privacy, compliance, or production risks early.

• Help Claspmates build with AI. Run programs such as AI Champs, Lattes with AI Labs, and Lunch & Learns, and pair with colleagues to turn ideas into shipped products.

• Keep learning as the field moves. Explore new models, products, and agent patterns, follow what is happening across the industry, and test what is genuinely useful.
  
  

What we’re looking for

• Evidence you can ship. You have built and shipped at least one tool/product/project beyond your own machine.

• Practical AI fluency. You actively use AI models and development tools. You can explain where they help, where they fail, what you verified yourself, and how you would evaluate quality in a real workflow.

• Full-stack range. You can reason about interfaces, backend logic, APIs and integrations, data flows, testing, and deployment. You do not need equal depth everywhere, but you can own a bounded feature end to end.

• Product judgment. You talk to users, clarify the decision the product should enable, choose the smallest useful version, and measure whether it worked.

• Fast learning. You ask for help with useful context, can operate with incomplete information, want coaching, and apply it.
  
  

You do not need to check every box above to apply. If you bring high agency, are ready to dive into unfamiliar problems, and are excited to learn as you go, we want to hear from you.

Interview process

The process is designed to understand how you build, think, learn, and collaborate—not to test trivia.

1. Hiring Manager call. A conversation with Harsh about completed work, product judgment, learning, and how you operate.

2. Technical assessment. A realistic, bounded engineering pairing session. AI tools are allowed; we care how you reason, build, debug, and verify.

3. Case study. A conversation about product thinking, scope, tradeoffs, communication, and taking an AI product from idea to adoption.

What we give in return

• Competitive cash and equity compensation.

• Health benefits, including medical, dental, and vision coverage.

• Student loan repayment benefits.

• 401(k) matching.

• Commuter benefits.

• Flexible PTO.

• Opportunities to grow with a fast-moving, mission-driven team.

Salary

The salary range for this position is competitive and will be commensurate with the candidate's experience, qualifications, and industry knowledge, ranging between $87,500 to $108,150 annually. In addition to the base salary, we offer an attractive equity component as part of our compensation package, providing an opportunity for eligible employees to share in the success and growth of our company. We are committed to offering competitive compensation and benefits packages to attract and retain top talent.


Remote Policy

To ensure smooth collaboration with the Boston-based team, we are limiting to Eastern/Central timezones with the expectation that it will be Boston hours. Additionally, they must be within 1 hour of a medium hub/ large airport with multiple daily flights to Boston. We are targeting the broader New England area to start as we expect that the candidate to have frequent travel to Boston for onboarding and ongoing collaboration.

Equal opportunity

Clasp is committed to creating a diverse and inclusive workplace where all employees feel valued, respected, and empowered to contribute their unique perspectives and talents. Clasp is an equal opportunity employer and prohibits discrimination and harassment of any kind. We provide equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.