Senior Technical Customer Success Manager - Enterprise, East

Anaconda, Inc.

6d•$96,000 - $139,000•Remote

About The Position

The Customer Success team at Anaconda is the primary relationship layer between our platform and the enterprise organizations that depend on it — from data scientists and ML engineers to IT architects and security teams managing open-source risk at scale. We help customers get real, measurable value from Anaconda's product suite by building trust, showing up prepared, and staying curious about what each customer is actually trying to solve. As a Senior Technical Customer Success Manager, you own a portfolio of strategic enterprise accounts and operate as the voice of the customer across the organization. You bring deep technical fluency (across Python packaging, environment management, and enterprise security and governance) and you use it to close the gap between what customers deploy and the value they actually realize. You're not here to just manage relationships. You're here to set the standard for how we engage technically and commercially, and to leave the function stronger than you found it. This role will cover an East Coast territory, so you will ideally be located in the EST time zone.

Requirements

6+ years in a technical customer-facing role. Customer success, technical account management, solutions engineering, or similar; with demonstrated ownership of a $6M+ book of business and accountability for retention and growth outcomes at large enterprise accounts (10,000+ employees)
Understanding of enterprise security and governance concepts relevant to Anaconda: CVE exposure, package provenance, air-gapped and private repo deployment, SSO, and gated registration
Experience with data science, ML, or developer tooling platforms. Databricks, Domino, Dataiku, SageMaker, or similar, and familiarity with how Anaconda fits into or alongside these environments
Ability to read logs and error output to triage technical issues before escalating to Support or Professional Services. You know the difference between self-resolving, routing to Support, and escalating to Product
Proven ability to build relationships across complex organizations, from practitioners to VP and C-suite stakeholders, and translate technical risk and product capability into executive-level business impact
Familiarity with adjacent and competitive tooling: SageMaker, Databricks, Snowflake, Vertex AI; sufficient to position Anaconda's complement-vs.-compete story credibly
Project management skills to coordinate multi-stakeholder technical engagements: onboarding, workshops, proofs of concept
Strong verbal and written communication across all levels of an organization, including executive audiences
AI fluency in daily work; comfortable using AI tools to research, document, prepare, and draft; rigorous about reviewing what you produce under your name before it reaches a customer
Bachelor's degree in a technical field or equivalent practical experience

Nice To Haves

Experience at a high-growth or early-stage company where the playbook wasn't written yet — you've helped build structure from scratch, operated with autonomy, and stayed effective when priorities shifted underneath you
Working fluency in Python packaging and environment management; conda, pip, pixi, and the tradeoffs between them — and the ability to hold a substantive technical conversation without SE support in routine scenarios
Deep familiarity with open-source ecosystems; software supply chain security, dependency management, license compliance exposure, and vulnerability workflows — and the ability to speak credibly to a CISO or VP Engineering about why it matters
A history of contributing to team infrastructure; playbooks, engagement templates, peer coaching, or process improvements that raised overall team performance, not just your own numbers
Experience in a high-growth, open-source, or data science-oriented company where customer needs evolve quickly and the product is still maturing
AI-enabled workflow contributions; you've built something others use, not just used AI for yourself; you've made a judgment call about where AI doesn't belong and explained why
You embody our values: Curious by Default, Build Together, Own It, and Lead with Guts and Heart — and our behaviors: Clarity, Care, and Candor
You care deeply about building environments where people of all backgrounds can do their best work

Responsibilities

Own a portfolio of enterprise accounts. Build deep relationships across complex organizations (from data scientists and platform engineers to IT architects, security leads, and C-suite stakeholders) well beyond the initial point of contact
Accelerate onboarding and initial adoption. Guide customers through first-use milestones: environment setup, CVE policy configuration, private repo and channel tokenization, and initial workflow adoption, coding assistant & quick start processes. Identify and resolve technical blockers before they threaten time-to-value
Drive ongoing usage health and consumption. Monitor seat utilization, package and channel usage, and admin portal signals to identify underused licenses, stalled users, or shadow IT risk. Proactively engage the AE when usage patterns suggest expansion opportunity or churn risk
Arrive at every customer interaction with a prepared point of view. Draw on product usage data, health scores, and technical signals to drive conversations forward and deliver clear value at each touchpoint
Own the technical inputs to account health scoring. Surface risk early (unresolved CVE exposure, blocked package access, unmanaged environments) and coordinate mitigation plans with the RM, Support, and FDE
Act as the voice of the customer to Product and Engineering. Channel technical requirements, competitive intelligence, and enhancement requests. Partner with Solutions Engineering on where Anaconda complements or competes with adjacent platforms in the customer's stack
Build the technical narrative for QBRs and executive engagement. Partner with the account team to document use cases, quantify value delivered (time saved, risk reduced, packages secured), and make the business case stick at the executive level
Support renewal and expansion. Bring technical proof points into renewal conversations (usage data, security posture improvements, workshop outcomes), advise the RM on churn forecast based on adoption and usage signals, and flag technical expansion whitespace; new teams, new use cases, adjacent workloads; to the AE for commercial pursuit
Use AI as a force multiplier. Build AI-enabled success approaches the team actually adopts. Know where AI belongs in the customer motion and where human judgment stays central. Your standard becomes the team's standard
Contribute to playbook development and team infrastructure. Senior TSMs are expected to leave the function stronger than they found it through documentation, engagement templates, peer coaching, and process improvements that raise overall team performance
Mentor and coach less experienced team members through account reviews, technical strategy sessions, and informal guidance. Translate personal experience into repeatable, teachable approaches
Operate within a Go-To-Market pod. Sit alongside the Account Executive, Renewal Manager, Solutions Engineer, and other pod roles (FDE, BDR, TAM where applicable) under a shared pod leader. Attend weekly pod and pipeline meetings and collaborate closely with the AE on account plans, customer relationships, and QBRs