Laurel

Product Marketing

• Develop strong technical command of the product: features, capabilities, integrations, and how they map to buyer needs.
• Build and maintain sales enablement assets — pitch decks, battlecards, one-pagers, demo scripts, and objection-handling guides — under the team's positioning framework.
• Translate technical capability into clear, value-based messaging for both technical and business audiences.
• Support competitive intelligence: track competitors and adjacent solutions, and keep battlecards and comparison material current.
• Partner with sales to understand field gaps and turn them into enablement content; help onboard and ramp reps on positioning.
• Contribute to solution briefs, data sheets, and feature launches.
• Keep enablement content organized, current, and easy for sales to find and use.

Product Marketing Manager

Marketing

• Own the regional outcome of the three campaign verticals across North America, against the Integrated Marketing Lead's strategy.
• Localize campaign content, assets, and experiences for the NA market and target accounts.
• Plan and run field activity: regional events, account-based programs, and in-market touchpoints aligned to the journey.
• Partner with sales in-region to align campaigns to pipeline priorities and target accounts.
• Coordinate with Brand and Product Marketing so campaigns carry the right voice, narrative, and positioning.
• Track campaign performance in-region and feed results back to Integrated Marketing and Growth & Analytics for optimization.

Integrated Marketing Manager

Full-stack Engineer

• Design, build, and maintain efficient, reusable, and extremely reliable code across the full stack.
• Take responsibility for complex features and product areas from spec through delivery.
• Work closely with cross-functional teams to gather requirements and deliver high-quality software.
• Identify bottlenecks and bugs and devise solutions to mitigate and address them.
• Mentor junior engineers and foster a culture of learning and growth.
• Implement automated testing and CI/CD pipelines to ensure robust releases.
• Participate in an on-call rotation with a detail-oriented approach.

Senior Full Stack Engineer

AI Engineer

• Own AI features end-to-end, from problem statement to GA
• Move features through our rollout tiers (prototype → design partner → beta → GA), earning each promotion with an eval baseline and a capacity plan
• Build and defend evals: golden datasets, a north-star metric per feature, and online monitoring — so we can *see and prove* how a feature behaves, not guess
• Lead the "meaning" layer of our semantic stack: retrieval semantics, embedding quality (proven first on initiative-candidate retrieval), and the label flywheel that feeds prompt optimization and golden sets. You co-design our vector and knowledge-graph stores with the AI Platform team — you're their most demanding customer
• Push output quality with the levers that matter: context assembly, prompt optimization, and per-customer/per-firm generation
• Work closely with cross-functional teams — product managers, designers, and other engineers — to gather requirements, define measures of success, and deliver high-quality solutions
• We want you not just to build but to *engage* with our product and our users. Your input and opinion will be highly valuable, and it is expected that you have many thoughts on how things should be done and why

Applied AI Engineer

Analytics Engineer

• Turn product and business data into clear, trustworthy insights leaders can act on.
• Own the analytics lifecycle—from ingestion and modeling to BI visualization and decision enablement.
• Deliver self-serve insights using SQL/Python and embedded BI (e.g., ThoughtSpot).
• Define the design patterns and data infrastructure to scale.
• Partner closely with the CX team to quantify and communicate Laurel’s ROI, and join customer-facing presentations.
• Apply machine learning to real-world product and business problems.
• Comfortable prototyping AI/ML models in notebooks, experimenting with approaches (classification, clustering, regression, NLP, etc.), and translating findings into actionable insights.

Senior Analytics Engineer / Data Scientist

Controller

• All accounting operations and close processes
• Scalable accounting policies, controls, and reporting infrastructure
• Audits and external accounting partner relationships
• Process automation and AI-enabled efficiencies across the finance function
• Building and developing the future accounting team
• Strategic partnership with the CFO and executive leadership on fundraising readiness

Infrastructure Engineer

• Own the architecture and technical strategy for internal automation systems — defining how the company's tech stack (HRIS, Okta, Salesforce, and others) connects, scales, and stays maintainable
• Architect and manage cloud-based infrastructure (AWS, GCP, or Azure) — including compute, networking, storage, and security
• Design and automate onboarding/offboarding workflows, including provisioning and deprovisioning access
• Own the architecture and lifecycle of internal AI tooling (e.g. Vercel, Supabase, Claude, ChatGPT— from evaluation through deployment, access governance, and deprecation
• Ensure proper access controls, least-privilege principles, and audit readiness across systems
• Establish CI/CD standards and error-handling patterns for automation systems so they're reliable, observable, and maintainable at scale

Staff Engineer – Automations and Infrastructure

Sales Operations Manager

• Onboarding: Own and continuously improve the new hire ramp program across Business Development, Sales, and Customer Success. Assess what works, cut what doesn't, and make it something people actually reference after their first month.
• Content and Pitch Library: Build and maintain a library of pitch decks, talk tracks, demo flows, and playbooks across buyer personas and use cases. Keep them current as the product and competitive landscape evolve.
• Certification: Design and run a rigorous certification program: rubric, scoring, and follow-through for reps who don't pass. Not a quiz but a rep-by-rep assessment with feedback loops.
• Coaching: Sit in on calls, debrief with sellers, run small group workshops. Be the person reps come to when a deal is stuck or a renewal is at risk and they need help sharpening their narrative.
• Competitive and Product Readiness: Translate new features, roadmap updates, and competitive moves into crisp seller briefs. Keep the team sharp without making them read documentation.
• Enablement Cadence: Win/loss reviews, deal storytelling sessions, rep spotlights, peer learning. Build the cadence of enablement that the team actually looks forward to.
• Cross-functional Partnership: Work closely with Product Marketing, RevOps, and Sales leadership to connect pipeline data, win/loss patterns, and field signals to enablement priorities. Be the voice of the field back to the business.

Sales Enablement Manager

Engineer

• Work directly with customers and Laureates to understand operational workflows, constraints, and technical environments
• Design and implement production-grade solutions across backend services, orchestration layers, integrations, and internal tooling
• Write high-quality code across the stack — typically TypeScript, APIs, data pipelines, and cloud infrastructure
• Own deployments end-to-end: discovery, architecture, implementation, testing, rollout, monitoring, and iteration
• Debug complex issues across customer systems, infrastructure, authentication, APIs, and data pipelines
• Collaborate closely with Product and Core Engineering to turn field learnings into reusable platform capabilities
• Rapidly prototype new functionality while maintaining strong engineering judgment around scalability and maintainability
• Translate ambiguous customer needs into clear technical plans and execution paths
• Help customers operationalize AI safely and effectively in real production environments
• Help accelerate the implementation team’s efforts to reduce time to impact for customers.