Customer Success Manager

Overview

You'll be the first or second CSM at Fluint, managing enterprise B2B SaaS customers who use their AI sales assistant, Olli, to close complex deals. You'll own the full lifecycle from onboarding through renewal and expansion, while simultaneously building out CS processes, playbooks, and strategy with the Head of CS.

Role Snapshot

Company Context

Stage: Seed (16 employees)

Size: Tiny - you'll know everyone

Growth: Actively hiring CS, which means they have customers to manage and are scaling post-product-market fit

Market Position: Early mover in AI sales enablement - category is hot but crowded with new entrants

What You'll Actually Do

Time Breakdown

Customer Onboarding (30%) | Account Management (25%) | Expansion Conversations (20%) | Building Processes (25%)

Key Activities

• Onboarding enterprise customers: Get sales teams configured on Olli, train reps on how to use the AI agent, troubleshoot integration issues, prove value in first 60 days before they decide it's shelfware
• Regular account check-ins: Weekly or bi-weekly calls with champions (likely sales ops, enablement, or sales leaders) to review usage, address issues, identify at-risk accounts
• Driving adoption: Your success depends on reps actually using Olli. You'll spend time analyzing usage data, running enablement sessions, creating internal champions, and fighting the "we paid for it but no one uses it" problem
• Expansion motions: Identify opportunities to expand seat count, add use cases, or upsell features. At this stage, you're probably working with AEs on expansion deals rather than closing them yourself
• Building the playbook: Document what works in onboarding, create customer health scoring, build QBR templates, define success metrics - you're inventing the CS function as you go

The Honest Reality

What's Hard

• Adoption is everything: You're selling AI to sales teams. Some reps will resist it, some will try it once and quit, some won't trust the AI. Your job is to get them over the hump, which requires persistence and creativity
• You're building the plane while flying it: There's no established CS playbook. You'll figure out onboarding as you onboard customers. QBRs will evolve. Success metrics will get refined. This is exciting for some people and chaotic for others
• Product is early: At 16 people, Fluint is still figuring things out. Customers will hit bugs, request features that don't exist, and push the product in directions it wasn't designed for. You'll spend time managing expectations and being the voice of the customer to product
• Renewals will be high-stakes: At enterprise price points with a small customer base, every renewal matters. You'll feel pressure on at-risk accounts
• Seed-stage uncertainty: No guarantees on runway, future funding, or market trajectory. You're betting on the company's ability to execute

What Success Looks Like

• High retention rate (90%+ logo retention, 100%+ net revenue retention with expansions)
• Customers show measurable improvement in deal velocity, win rates, or sales productivity from using Olli
• New customers get to value fast (active usage in first 30 days, not just "kicked off")
• You've documented repeatable onboarding and QBR processes that can scale as the team grows
• Expansion pipeline contributes meaningfully to ARR growth

Who You're Working With

Primary Contacts at Customer Accounts:

• Sales Operations / RevOps leaders (they likely evaluated and bought Fluint)
• Sales Enablement / Sales Managers (they drive adoption with reps)
• Individual AEs or sales reps (end users who need to actually use Olli)

What They Care About:

• Does this AI actually save time or is it more work to maintain?
• Can we trust the AI's output or do reps need to double-check everything?
• Are we seeing measurable improvements in pipeline, velocity, or win rate?
• Is this easy enough that our team will actually adopt it?

Requirements

• Experience doing enterprise CS at a B2B SaaS company (they want someone who's done this before, not learning on the job)
• Comfortable with full-stack CS - you've owned onboarding, adoption, renewals, and expansion in previous roles
• Willing to build processes from scratch in a seed-stage environment (this rules out people who need structure and established playbooks)
• Technical enough to understand AI/ML sales tools and help customers troubleshoot (not engineer-level, but more technical than average CSM)
• Sales context helps - understanding how sales teams work, what reps care about, how deals move through pipelines