Preparing for an interview at Harvey requires a balanced approach that demonstrates both your technical capability and your client-facing polish. You should be ready to showcase your understanding of the legal tech landscape, enterprise software deployment, and generative AI concepts.

Role-Related Knowledge – You must understand the fundamentals of LLMs, prompt design, and enterprise software architecture. Interviewers will assess how comfortably you can discuss technical concepts and whether you can translate them into business value for legal professionals.

Problem-Solving Ability – Harvey values candidates who can approach ambiguous client challenges with structure and analytical rigor. During your case study and technical rounds, focus on explaining your methodology, making reasonable assumptions, and presenting clear, data-driven recommendations.

Leadership & Influence – As a Customer Success Engineer, you will need to guide clients through significant change management. You must demonstrate the ability to build consensus, influence senior stakeholders, and advocate internally for client needs with product and engineering teams.

Culture Fit & Adaptability – Operating in a fast-paced, high-growth startup environment requires resilience, proactivity, and comfort with ambiguity. Show your interviewers that you are self-directed, eager to learn, and passionate about the transformative potential of AI.

The interview process for the Customer Success Engineer role at Harvey is rigorous, transparent, and highly structured, typically spanning several weeks. The company aims to evaluate both your technical depth and your executive presence through a series of conversational and practical assessments. Candidates can expect a high-touch process, though communication times can occasionally vary depending on hiring volume.

The journey begins with a standard recruiter screen to align on your background, career goals, and compensation expectations. Following this, you will have a deeper conversation with the hiring manager—often the Customer Success Lead—focusing on your relevant experience, technical aptitude, and understanding of the Customer Success Engineer role. This stage is designed to ensure alignment on the role's expectations before moving to the intensive onsite loop.

The final stage is a comprehensive onsite interview sequence (often conducted virtually or in-person depending on location) consisting of four back-to-back 30 to 45-minute sessions. These rounds cover behavioral questions, cross-functional collaboration, and a live case study presentation. You will present a pre-prepared slide deck to a panel of customer success managers and cross-functional team members, simulating a real client engagement.

The visual timeline above outlines the typical progression from your initial application to the final decision. Candidates should use this sequence to pace their preparation, focusing first on high-level behavioral alignment before diving deep into technical case study preparation. Note that while the process is highly standardized, the timing between the hiring manager screen and the onsite loop can sometimes take longer due to coordinating panel availability.

To succeed in the Harvey interview loop, you must understand the specific competencies the hiring team evaluates during each round.

The Case Study Presentation

The case study is the cornerstone of the onsite interview loop and carries significant weight in the final hiring decision. You will receive the prompt in advance, giving you ample time to conduct meaningful preparation and build a professional presentation.

Be ready to go over:

• Strategic Structuring – How to organize a 10-12 slide deck that addresses client pain points, technical implementation, and adoption strategy.
• Executive Presence – Delivering a polished, confident presentation to a panel of three to four interviewers, some of whom may join virtually.
• Handling Q&A – Anticipating and confidently answering tough, unexpected questions from the panel during and after your presentation.
• Advanced concepts (less common) – Creating custom deployment roadmaps, designing risk mitigation frameworks for AI adoption, and outlining API integration architectures.

Example scenarios:

• "Present an onboarding and expansion strategy for a major enterprise client that has historically struggled with software adoption."
• "Pitch Harvey's security and data privacy architecture to a skeptical corporate legal IT department."
• "Propose a structured prompt-engineering framework to help a client automate a highly manual document review process."

Technical Integration & Legal AI Domain

This evaluation area focuses on your technical literacy and your ability to act as a trusted technical advisor to highly sophisticated clients.

Be ready to go over:

• Generative AI Fundamentals – Understanding how LLMs generate text, the role of context windows, and the mechanics of retrieval-augmented generation (RAG).
• Technical Troubleshooting – Walkthroughs of how you isolate and resolve technical issues, such as API latency, authentication failures, or integration bugs.
• Data Security & Privacy – Understanding SOC 2, ISO 27001, data encryption, and zero-data retention policies as they apply to enterprise SaaS.

Example scenarios:

• "A client reports that the AI model is consistently missing key clauses in a specific type of contract. How do you troubleshoot this?"
• "Explain to a client's security team how Harvey handles their proprietary data and ensures it is not used to train public models."

Client Management & Change Management

This area tests your soft skills, emotional intelligence, and ability to guide conservative organizations through major technological transformations.

Be ready to go over:

• De-escalation Strategies – Managing frustrated clients, aligning expectations, and turning negative experiences into positive outcomes.
• Adoption Playbooks – Designing training programs, identifying internal champions, and driving weekly active usage across diverse teams.
• Cross-Functional Advocacy – How you capture client feedback and effectively convey it to product managers and engineers to influence the roadmap.

Example scenarios:

• "Describe a time you had to tell an important client 'no' regarding a custom feature request."
• "How do you handle a situation where the executive sponsor is excited about Harvey, but the day-to-day users are resistant to using it?"

As a Customer Success Engineer at Harvey, your primary mission is to ensure that enterprise clients realize maximum value from the platform. You will own the technical relationship post-sale, guiding clients through the crucial stages of onboarding, implementation, and ongoing optimization. This involves deeply understanding their legal workflows and identifying opportunities where Harvey's AI can drive efficiency and accuracy.

On any given day, you will run training sessions for hundreds of legal professionals, write custom prompts to solve specific legal use cases, and collaborate with IT departments on secure integrations. You serve as the primary feedback loop between Harvey's most strategic clients and the internal product team. By translating complex user behaviors and technical friction points into structured product feedback, you directly influence the product roadmap.

You will also work closely with account executives and customer success managers to identify expansion opportunities. By monitoring usage metrics and proactively conducting business reviews, you help clients scale their usage from small pilot groups to firm-wide deployments. Your technical expertise and consultative approach are critical to maintaining Harvey's high retention rates and driving net revenue retention.

To be competitive for the Customer Success Engineer position at Harvey, candidates must demonstrate a unique blend of technical acumen, client-facing mastery, and domain interest.

• Must-have skills – Strong technical literacy, including a solid understanding of APIs, SaaS integrations, and generative AI concepts (LLMs, prompt engineering). Exceptional presentation and communication skills, with a proven track record of presenting complex topics to executive-level stakeholders.
• Nice-to-have skills – Prior experience working within or selling to the legal industry (law firms or corporate legal departments). Background in software engineering, technical consulting, or solutions architecture. Familiarity with Python, SQL, or data analysis tools.
• Experience level – Typically 3 to 6 years of experience in a highly technical customer-facing role, such as a Solutions Engineer, Technical Account Manager, or Customer Success Engineer at a fast-growing enterprise SaaS company.