Senior / Team Lead Customer Success Manager

CS-Society; Bengaluru; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

Nexla, based in Bengaluru with a hybrid work model (2 days in office), offers an equity-inclusive compensation structure. The Customer Success role balances owning enterprise accounts with mentoring CS professionals, guiding onboarding and long‑term adoption, and shaping the customer journey across Sales, Solutions, Engineering, and executive leadership.

You’ll work in a lean, high‑impact team, manage escalations, and drive health metrics and renewal strategies.

Qualifications

• 12+ years in customer success management, engagement management, or related roles in B2B SaaS.
• Experience bridging business teams and engineering.
• Experience building scalable CS playbooks and health-score systems.

Responsibilities

• Own a portfolio of 10–15 strategic enterprise accounts from onboarding to renewal.
• Coach and mentor CSMs, own CS playbooks and health-score frameworks.
• Maintain executive relationships with CIO/VP data owners and AI steering committees.
• Lead escalations and coordinate with engineering and leadership to resolve critical issues.

Skills

Customer Success

Enterprise accounts

Coaching & mentoring

Executive relationships

Escalation management

Data operations depth

AI/GenAI familiarity

Cross-functional collaboration

Job description

Nexla is a private company. Nexla is the data layer for enterprise AI. The platform gives AI applications and agents the connectivity, context, and governance to operate across 1,000+ enterprise systems in real time. Its MCP Studio lets teams build task-specific, governed MCP servers conversationally, while the Helix Context Layer grounds every agent interaction in an enterprise's systems, data, schemas, documentation, and business logic. Nexla processes more than 10 trillion records and actions annually and is trusted by Fortune 100 enterprises.

Innovators like Autodesk, DoorDash, Johnson & Johnson, Instacart, LinkedIn, and LiveRamp rely on Nexla to ensure mission-critical data flows seamlessly across the enterprise. Recognized four years running in the Gartner® Magic Quadrant™ for Data Integration Tools and rated 4.9/5 on Gartner Peer Insights™, Nexla delivers reliable, scalable, agentic data integration. Founded in 2016. It has 74 employees. Annual revenue is $10.2M.

Description

Nexla, briefly

Nexla is the data layer for enterprise AI. We give AI apps and agents the connectivity, context, and governance to work across more than 1,000 enterprise systems in real time, and we process over a trillion records a month doing it. DoorDash, LinkedIn, Johnson & Johnson, Instacart, and LiveRamp run mission-critical data on us. Honorable Mention in the Gartner Magic Quadrant™ for Data Integration Tools, and top-rated by customers on Gartner Peer Insights four years running. Founded 2016, remote-first, headquartered in San Mateo.

Our values are short and we actually use them: Have Empathy. Be Curious. Be Intellectually Honest. Achieve Excellence. Remember to Relax.

Role, briefly

Our Customer Success team owns the end-to-end client experience, from initial integration through enterprise adoption and expansion. It is a small team, and this role does two jobs at once: running your own enterprise accounts, and leading, mentoring, and coaching the CSMs around you. You work closely with Sales, Solutions, Engineering, and executive leadership, and you are the primary voice of the customer internally, including on where the platform goes next.

Our Customer Success team owns the end-to-end client experience, from initial integration through enterprise adoption and expansion. It is a small team, and this role does two jobs at once: running your own enterprise accounts, and leading, mentoring, and coaching the CSMs around you. You work closely with Sales, Solutions, Engineering, and executive leadership, and you are the primary voice of the customer internally, including on where the platform goes next. As part of a lean and high-impact team, you will directly manage a portfolio of 10-15 strategic enterprise accounts, guiding them through both initial onboarding and long-term customer success.

What you'll own

• Retention and expansion across your accounts. That starts at onboarding, overseeing complex implementations alongside our Solutions Engineers and Architects, including vector pipeline setup into existing customer infrastructure, and runs through renewals, upsells, and SOWs with Sales.
• The standard of work across the CS team. Coaching and mentoring the CSMs, and owning the playbooks, health-score frameworks, and retention strategies they run on. The function has to scale as the company grows.
• Executive relationships at your accounts. C-level sponsors, VP-level data owners, and AI steering committees, aligned on business value and ROI. You run the Executive Business Reviews and technical workshops.
• What happens when things go wrong. You are the escalation point for critical issues, technical roadblocks, and at-risk accounts, pulling in engineering and leadership and keeping it calm.

AI tooling is part of the job here, not a side interest. Customer communication, health tracking, and account reporting are all places we expect you to use it.

Ninety days : You will have fully onboarded your initial pod of strategic enterprise accounts, audited and leveled up our CS playbooks. You will have joined key customer calls to assess health across your 10–15 enterprise accounts, identified the next set of strategic and tactical deliverables for each, and established clear coaching cadence and updated playbooks for the team.

The hard problem

Because Nexla's enterprise platform bridges deep data engineering (ETL/ELT, APIs, streaming) with cutting-edge AI architectures (agentic workflows, RAG, and MCP servers), the core tension in this role is balancing technical execution with high-level value creation.

Must-haves

• 12+ years in customer success management, engagement management, technical delivery, professional services, or sales engineering, in B2B SaaS.
• Background in solutions engineering, sales engineering, or technical consulting where you acted as a bridge between business teams and engineering.
• Experience establishing or scaling early-stage Customer Success frameworks (e.g., building playbook templates, health-score scoring systems, or churn-risk matrixes).
• Track record of identifying expansion opportunities (upsells/cross-sells) and collaborating closely with Account Executives/Sales to close them.
• You have led, mentored, or managed team members and driven team-wide KPIs.
• You have built, negotiated, and held relationships with C-suite and senior enterprise stakeholders.
• You have run high-stakes escalations and de-escalated risk inside complex enterprise dynamics.
• Real technical depth in data operations and data engineering pipelines (ETL and ELT), plus modern AI paradigms: GenAI, retrieval-augmented generation, vector databases, and LLM data flows.
• You use AI tools in your actual work and can say specifically where they help and where they mislead you.

You’ll thrive here if

• You lead from the front. You carry your own accounts while raising the standard of the people around you.
• You challenge the status quo rather than inherit it. The playbooks here are yours to rewrite.
• You are comfortable in a high-stakes executive conversation and in a technical one about pipeline architecture, often on the same day.
• You can hold a lot of cross-functional threads at once and still hit the dates you committed to.

One thing to be clear about: this is a small team, so you carry accounts as well as leading. If you are looking for a pure people-management role, this is not it.

How we hire

• Hiring Manager - VP Of Customer Success - Customer Engagement, Team and culture fit
• Lead Solutions Architect - Technical understanding
• CRO - Revenue understanding, cross selling & upselling, collaboration with Sales & PreSales
• Group Presentation - Lead a discovery, escalation or kickoff call with Stakeholders

The practical stuff

Bengaluru, hybrid, 2 days a week in office. Compensation includes base salary and equity, set by depth and experience rather than by title. Working hours: the previous version of this role required US West Coast coverage.

Why Nexla? Why now?

A few large companies - DoorDash, SentinelOne, Johnson & Johnson, LinkedIn, Amex, Integrity Marketing, among them use Nexla for data integration. Connectors, runtime, transformations, scheduling, the parts of the stack where data has to move between systems reliably.

The reason this is an interesting moment to join is what the agent shift is doing to the category. Data integration used to mean "land this data in that warehouse so a human can look at it." That product is mature. What it's becoming is closer to "an agent asks a business question, and the platform figures out which data and what code and which APIs add up to a real answer." That's a much bigger problem, and most of the architecture for it hasn't been built yet by anyone.

A concrete example. A revenue team wants to ask "which enterprise customers are showing renewal risk" and get a real answer through whatever agent or app they work in. Today there is no clean way to answer that question, it requires CRM, usage, support, and billing data joined in org-specific ways, and the calling agent can't just invoke a tool that returns the right answer unless someone first establishes whether the underlying data is even capable of producing one.

That is the system we are building. A probe agent investigates the data plane whether the right fields are populated, whether freshness is adequate, whether the joins exist, whether credentials cover the required scope and returns a grounded feasibility answer. Where there are gaps, Express.dev composes the pipelines to close them. The capability is then exposed as an MCP server: "renewal risk" as a curated product, with the business logic correct and the query semantics described well enough that the calling agent uses it as intended. The MCP Gateway governs which agents can call which capabilities, with the policies, audit, and observability an enterprise control plane requires.

The bet is that ten years of connector work, an enterprise customer base, and a runtime that already moves real volume are the right foundation to define this layer from.