Full-Stack Marketer

Nexla, Bengaluru, Karnataka, India +1

What you will do

Organic visibility for data integration and AI keywords. SEO strategy, the technical work behind it, and the content that actually ranks.
Paid and ABM. Google Ads and LinkedIn Ads from audience targeting through creative, plus the account-based programmes aimed at enterprise prospects.
The funnel. Website performance and user behaviour, where people drop and why, the marketing automation workflows and lead scoring behind it, and the reporting that says which channel earns more budget and which one stops.
The content engine. Blogs, whitepapers, case studies, social across LinkedIn and X, video scripts, and webinar material. Technical enough that a data engineer keeps reading, clear enough that the person signing the contract finishes it.

AI tooling runs through all of it: content production, competitive and market research, segmentation, and the triggers behind automated campaigns.

Ninety days in: You would have helped revamp our inbound traffic and conversions to bring in more demo requests and help improve conversion.

The hard problem Most of the traffic today is organic and direct. The hard problem is to make the website an organic lead engine consistently aligning top topics with content needed and SEO/ AEO optimization to drive more qualified traffic and better engagement and conversions. .

All jobs

Full-Stack Marketer

Nexla, Bengaluru, Karnataka, India +1

What you will do

Organic visibility for data integration and AI keywords. SEO strategy, the technical work behind it, and the content that actually ranks.
Paid and ABM. Google Ads and LinkedIn Ads from audience targeting through creative, plus the account-based programmes aimed at enterprise prospects.
The funnel. Website performance and user behaviour, where people drop and why, the marketing automation workflows and lead scoring behind it, and the reporting that says which channel earns more budget and which one stops.
The content engine. Blogs, whitepapers, case studies, social across LinkedIn and X, video scripts, and webinar material. Technical enough that a data engineer keeps reading, clear enough that the person signing the contract finishes it.

AI tooling runs through all of it: content production, competitive and market research, segmentation, and the triggers behind automated campaigns.

Ninety days in: You would have helped revamp our inbound traffic and conversions to bring in more demo requests and help improve conversion.

Worth a look before you apply

What we are building now. MCP Studio and Express, our latest innovation.
Who uses us, and why. nexla.com/customers
What we publish. nexla.com/blog
Our CEO on why we take "Remember to Relax" seriously. Read the founder story
Everything else. nexla.com · All open roles

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.

Full-Stack Marketer

What you will do

Full-Stack Marketer

What you will do

What you need

Must-haves

You'll thrive here if

Nice to have

Worth a look before you apply

About Nexla

Similar jobs at other companies

Senior Software Engineer - AdTech Bidding Platform / Traffic Shaping Specialist

Product Owner | Mid | Web

Backend AI Engineer

Backend AI Engineer

Engineering Manager | Senior | Knowledge

Applied AI Engineer

Nexla