Gradient Labs

Member of Technical Staff

Remote, United States remote Entry Salary not listed
remote Technology & IT Curated
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About the role

At Gradient Labs, we're building the AI customer operations platform for financial services.
Founded in 2023, we now work with some of the biggest names in banking and fintech. Our platform runs specialist agents, purpose-built for financial services, to eliminate manual work across customer support and back-office operations. Together, they give product and operations teams the visibility and control to trust every outcome.
We're a team of builders from companies like Monzo, Wise, Mastercard, Revolut and Google. If you're excited to tackle some of the hardest problems in AI and help shape the future of customer operations, we'd love to hear from you.
🎯 How you’ll make an impact
This is a build-and-ship role. You'll turn ambiguous customer support problems into reliable, observable AI agents that handle live conversations for real users. You'll work close to production — designing prompts and tool flows, building eval suites, shipping changes, watching what breaks, and iterating fast.
Build and operate AI agents in production: Design, implement, and maintain agentic systems powered by LLMs — handling tool calling, multi-step reasoning, and integration with customer APIs and data sources. You'll own these systems end-to-end: reliable, observable, and auditable from day one.

Translate business problems into agentic workflows: Work directly with enterprise customers to understand their workflows, surface the highest-leverage automation opportunities, and frame them as well-scoped agent problems with clear success criteria. You'll be the technical counterpart in customer conversations, turning ambiguity into a concrete plan.

Build robust evaluation infrastructure: Create and maintain eval suites drawn from real-world scenarios and edge cases. Go beyond vibes-based testing: structured evals measuring accuracy, safety, and latency, tied to clear business outcomes, used to drive systematic improvements to prompts, tools, and behaviour.

Enhance our agent: Develop, evaluate, and optimise the skills that make up our agent. Curate datasets, iterate on improvements, test changes, and ship successful approaches into production.

Shape our internal AI platform: Contribute to shared libraries, patterns, and standards for how we build, evaluate, and deploy agents across customers. Help define how we approach prompting, tool orchestration, retrieval, and monitoring.

Experiment and prototype: Keep up with the latest in NLP, agentic systems, and generative AI. Prototype against our hardest problems with a bias toward shipping experiments quickly rather than long research cycles.

Analyse data: Work across customer queries, support tickets, and related data to find patterns and identify what our agents could automate next.

Drive technical decisions: Scope your own work, push back when the framing is wrong, and tell us when the plan needs to change.

💡 What you’ll bring
4+ years of professional software engineering experience, with a meaningful focus on Machine Learning, NLP, or applied AI.

End-to-end ownership of production systems: you've designed it, shipped it, watched it break, and iterated. You can point to specific moments where you drove a decision forward.

Hands-on experience shipping LLM-based features or agent systems into production, not just prototypes. Go experience a plus.

Strong Python skills: clean, testable, observable production-grade code.

You're always automating. Your default reaction to a repetitive task is to build something for it.

Comfort reasoning about trade-offs (accuracy vs latency, coverage vs precision, cost vs quality), framed around what matters to the user and the business.

A product-driven posture: you've worked closely with PMs, customers, or domain experts, and translated ambiguity into shipped solutions without needing a perfect spec.

A preference for fast iteration over long research cycles.

Why join Gradient Labs?
This is a unique chance to be part of a team working with cutting-edge technology to reshape how businesses will operate in the future. Over the next 10 years, every company will need to embrace AI-powered operations to stay competitive, and this role puts you right in the middle of that transformation.
You’ll tackle challenging and new problems, work with some of the most exciting brands across different industries, and be surrounded by a passionate, smart team that’s driven to build something groundbreaking.
Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Role
Technology & IT API integration Customer Service Figma Operations Python remote

Likely questions

  1. Tell us about work you have done that is close to the Member of Technical Staff role.
  2. How would you approach your first 30 days at Gradient Labs?
  3. Which of API integration, Customer Service and Figma have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with API integration, Customer Service and Figma.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Member of Technical Staff role because I can bring practical experience in API integration, Customer Service and Figma, learn the team quickly, and contribute to the outcomes Gradient Labs needs from this hire.

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