Own the production pipeline for Xsolla Mall's co-branded page model — the operational infrastructure that allows new page configurations combining games, payment partners, creators, and brands to be built, QA'd, and launched at increasing volume as the partner ecosystem grows.
Develop and maintain templating frameworks, build workflows, and launch coordination processes that bring consistency and repeatability to page production without requiring bespoke effort for every new configuration.
Work closely with the Senior Manager, Xsolla Mall Marketing to ensure the production pipeline reflects current campaign and partner priorities, and that page launches are coordinated with marketing programming.
Partner with the Content & Marketplace Operations Manager (Ops) to ensure operational execution on Mall surfaces is integrated with — not siloed from — the broader production architecture.
Identify where page production bottlenecks exist and design automated or semi-automated solutions that remove them.
Map marketing workflows across XPN, Lightstream, and Mall — identifying where automation can improve speed, consistency, and throughput.
Design, build, and maintain automated workflows that reduce manual effort on repeatable tasks: campaign intake and routing, content scheduling, performance alerts, reporting, and cross-functional notifications.
Partner with the Director of Marketing to surface friction points in the team's operating model and build the automation infrastructure that resolves them — ensuring that process improvements compound over time rather than requiring constant re-invention.
Work alongside the XPN Operations & AI Lead to ensure that automation built for marketing is coherent with the broader operational infrastructure across the Partner Network, and that shared tools and workflows are leveraged rather than duplicated.
Maintain clear documentation of all active automations — what they do, what systems they connect, and how they are monitored — so the team can rely on them with confidence.
Support the measurement infrastructure that tracks the marketing team's contribution to Xsolla's performance framework — the output-based metrics that connect marketing activity to business outcomes across XPN, Lightstream, and Mall.
Automate the data flows that feed marketing performance reporting — reducing the manual effort required to produce accurate, timely dashboards for the VP of Marketing, Marketing Director, and Finance stakeholders.
Partner with the BI and Data teams to ensure marketing outputs are correctly captured and attributed across systems including Jira, Braze and relevant analytics platforms.
Build alert systems and monitoring tools that surface performance anomalies early — so the team can respond to signals rather than react to results after the fact.
Ensure reporting outputs are clear, auditable, and accessible to stakeholders who need to interrogate the data without requiring a manual walkthrough each time.
Serve as the marketing team's primary advocate and practitioner for AI tooling — staying current on what is available, evaluating fit for the team's specific needs, and driving adoption of tools that deliver genuine operational value.
Evaluate and recommend AI platforms and integrations across the marketing stack — assessing capability, integration complexity, and cost before committing to new tooling.
Build practical enablement for the team: workflow templates, prompt frameworks, and working examples that raise AI fluency across functions without requiring deep technical expertise from every team member.
Leverage Xsolla's internal AI capabilities — including platform integrations across Atlassian, Slack, and other operational tools — to ensure Marketing is making full use of infrastructure already available.
Requirements
7–10 years of experience in marketing operations, marketing technology, or a closely related field — with hands-on accountability for building and maintaining automation systems in a marketing or platform context.
Demonstrated experience designing and deploying automated workflows that run reliably in production — not just prototypes or experiments, but systems the team depends on day-to-day.
Proficiency with AI and automation tooling (including LLM-based platforms and workflow orchestration tools such as n8n or equivalent) — able to move from identifying an opportunity to building a working solution independently.
Strong analytical capability: comfortable working with marketing performance data, partnering with BI teams on reporting infrastructure, and identifying when data quality or attribution logic is wrong before it reaches stakeholders.
Strategic thinking alongside craft excellence — able to contribute a point of view on how the marketing function should evolve operationally, not just execute within the system as it exists.
Able to operate with genuine autonomy: identifying the highest-leverage problems without being directed to them, and building solutions with enough documentation and discipline that they outlast your direct involvement.
Clear communicator across technical and non-technical audiences — able to explain automation decisions and performance frameworks to the VP of Marketing, Finance, and cross-functional partners without requiring a technical background to follow.
Experience with Jira at an administrative or automation level — workflow rules, tagging systems, dashboard configuration, and API integrations.
Familiarity with marketing CRM platforms (Braze, Mailchimp, or equivalent) at the integration and data model level rather than just as an end user.
Background in gaming, SaaS, or platform marketing environments — an understanding of creator ecosystem dynamics or subscription-based product marketing is a genuine asset, though not a requirement.
Experience with BI or analytics tooling (Looker, NeoDash, or similar) sufficient to collaborate on data model design and validate that ingestion logic is producing accurate outputs.
Track record of raising AI or automation fluency across a non-technical marketing team through practical enablement rather than theory.
Exposure to multi-agent or orchestrated automation patterns — where discrete automated steps hand off between each other rather than a single workflow handling everything end-to-end.