Senior Technical Customer Success Manager - Enterprise, East

We need to output HTML fragment with sections: About the role? The posting includes "About Anaconda" then "Summary", then "What You’ll Do", "What You’ll Need", "What Will Make You Stand Out", "Why You'll Like Working Here". Also includes salary and benefits details. We need to use

for section headings (e.g., About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). However we must only include sections when posting has real specific content. We can map sections: "About the role" maybe corresponds to Summary? Or we could use "About the role" heading for the summary. "Responsibilities" for What You’ll Do. "Requirements" for What You’ll Need. "Qualifications" maybe for What Will Make You Stand Out? Or Skills? Benefits and Pay sections: we have benefits and salary info. So we can include Benefits and Pay sections. Schedule not present, so omit. We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, privacy notice, etc. Also remove application deadline line? That's maybe considered application instructions? It says remove application instructions. The deadline line is part of application instructions? Probably remove. Also remove "An Equal Opportunity Employer..." etc. Remove privacy notice. Remove "Anaconda, Inc...." etc. We need to preserve all substantive information. So we need to keep the description of Anaconda, summary, responsibilities, requirements, standout, why you'll like working here, benefits, salary. We must not invent or summarize away detail. Keep details. We need to use

• for any list of duties/requirements/benefits. So for responsibilities we should list bullet points. For requirements also bullet list. For benefits also bullet list. For "What Will Make You Stand Out" maybe also bullet list. For "Why You'll Like Working Here" maybe bullet list. We need to use

  for prose. We must not include sections with filler like "commensurate with experience". Not relevant. We need to output only HTML fragment, no /, no markdown fences. Let's craft. First, maybe a short paragraph for metadata? Could include location? The posting mentions "This role will cover an East Coast territory, so you will ideally be located in the EST time zone." That's substantive; we could put in a

  under About the role or maybe as a note. Not a heading. We'll structure:

  About the role

  [summary paragraph about Anaconda and the role]

  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
  ... etc. Need to split each bullet as separate
  • . The responsibilities list is long; we need to break into items. We'll copy each sentence or clause as separate
  • . Ensure we keep all details. Similarly for Requirements (

    Requirements

    ) with bullet list. For What Will Make You Stand Out maybe as

    Qualifications

    or

    Skills

    . The instruction says use headings like Skills, Benefits, Pay, Schedule. But we can also use Qualifications. It says use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can use Qualifications for standout. Skills maybe for something else but we may not have separate skills. We'll use Qualifications for standout. Benefits:

    Benefits

    with bullet list. Pay:

    Pay

    with paragraph containing salary range and variable commission, equity. We should not include Schedule. We need to ensure we don't include any boilerplate like EEO, privacy, etc. Let's extract the content. First, About Anaconda paragraph: "Anaconda is built to advance AI with open source at scale, giving builders and organizations the confidence to increase productivity, and save time, spend and risk associated with open source. 95% of the Fortune 500 including Panasonic, AmTrust, Booz Allen Hamilton and over 50 million users rely on the value The Anaconda AI Platform delivers through a centralized approach to sourcing, securing, building, and deploying AI. With 21 billion downloads and growing, Anaconda has established itself as the gold standard for Python, data science, and AI and the enterprise-ready solution of choice for AI innovation. Anaconda is backed by world-class investors including Insight Partners. Learn more at https://www.anaconda.com." Then Summary: "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." We can combine About Anaconda and Summary into About the role section prose. Now Responsibilities bullet list: Let's extract each bullet from "What You’ll Do". The text: "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" We need to split each line into separate
  • . Some lines contain multiple sentences; we could keep them as one
  • each. That's fine. Now Requirements bullet list from "What You’ll Need": "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" We'll make each line a
  • . Now What Will Make You Stand Out bullet list: "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" We'll put each as
  • under Qualifications. Now Why You'll Like Working Here bullet list: "You'll thrive in a high-performance environment where results are recognized and rewarded Your work directly contributes to shaping the future of data science, machine learning, and AI in the enterprise. You'll work alongside a collaborative team that values diverse, thoughtful discussion, clarity and candor. You'll be supported by a culture that puts employees first - with flexible hours, a fully remote setup,