PRAGMATIKE

• Own paid user acquisition across Meta, TikTok, Google, and additional acquisition channels. • Manage campaign structure, budgets, bidding strategies, audience targeting, and placements. • Lead creative testing by evaluating assets from internal creative and UGC teams, scaling high-performing campaigns and quickly iterating on underperforming ones. • Optimize the complete acquisition funnel from ad click to subscription conversion, focusing on CAC, ROAS, LTV, and payback. • Scale marketing spend while maintaining strong acquisition efficiency. • Own attribution and measurement across mobile acquisition, including MMPs, SKAdNetwork, deep linking, and post-ATT performance analysis. • Partner with product and leadership to improve onboarding flows, landing experiences, and conversion rates. • Report campaign performance using clear metrics and actionable insights. • Continuously experiment with new audiences, creatives, and acquisition opportunities.

• Lead the end-to-end production of UGC and short-form video content for paid and organic social campaigns. • Generate creative concepts, write scripts, storyboards, hooks, captions, and platform-native copy in English. • Source, brief, and manage creators, influencers, actors, and production partners. • Direct video shoots from planning through final delivery, including casting, locations, props, and on-set creative direction. • Build scalable production workflows that enable high-volume content creation while maintaining quality. • Manage relationships with external agencies, production vendors, and UGC platforms. • Collaborate closely with product, growth, and marketing teams to rapidly test new creative concepts. • Analyze campaign and creative performance to continuously optimize future content. • Stay ahead of social media trends, competitor campaigns, and emerging content formats.

• Own the product growth roadmap across acquisition, activation, retention, referral, and monetization. • Design, prioritize, and execute experiments to improve key product and business metrics. • Partner closely with engineering, design, marketing, data, and leadership to deliver growth initiatives. • Analyze user behavior and product performance to identify opportunities for optimization. • Define product requirements, success metrics, and rollout strategies for new features. • Improve onboarding flows, subscription conversion, engagement loops, and user retention. • Work alongside performance marketing teams to optimize acquisition funnels and post-install experiences. • Monitor experiment results, iterate quickly, and scale successful initiatives. • Communicate product strategy, priorities, and outcomes across cross-functional teams.

• Design and animate high-performing video advertisements and UGC-style creatives for paid social campaigns. • Develop creative concepts, hooks, and visual storytelling ideas from initial concept through final delivery. • Produce content for Meta, TikTok, YouTube, and emerging acquisition channels. • Experiment with a wide range of creative styles, from polished motion graphics to native social content. • Deliver a continuous pipeline of creative assets and variations optimized for rapid testing. • Collaborate closely with producers, growth marketers, and user acquisition teams to improve campaign performance. • Analyze creative performance and iterate based on engagement and conversion data. • Maintain a consistent visual identity while continuously exploring new creative directions. • Contribute ideas that improve creative workflows, production quality, and campaign effectiveness.

• Build and operate production-grade model serving infrastructure using frameworks such as vLLM, TGI, Triton, or equivalent • Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models • Develop and maintain auto-scaling systems, multi-model serving architectures, and intelligent request routing layers • Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance • Design observability systems for tracking inference latency, throughput, GPU usage, cost metrics, and system health • Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments • Own the full lifecycle of ML systems from development through production, including operational support and on-call responsibilities • Define engineering best practices and contribute to platform scalability in a fast-moving startup environment

• Design, develop, and maintain scalable backend services using NestJS • Architect APIs, caching layers, queues, and distributed services for high-performance SaaS applications • Build and maintain integrations with third-party systems using REST APIs (SOAP experience is a plus) • Collaborate closely with frontend and product teams to deliver end-to-end product features • Improve application performance, reliability, scalability, and maintainability • Contribute to engineering best practices, code quality, and technical architecture decisions • Leverage AI-assisted development workflows to accelerate implementation, testing, and debugging • Take ownership of features from design through production in a fast-moving startup environment

• Build, maintain, and optimize secure, scalable AWS infrastructure supporting production applications • Design and implement Infrastructure as Code using Terraform, Terragrunt, Ansible, and related automation tools • Develop and maintain CI/CD pipelines to enable reliable and automated software delivery • Manage containerized workloads using Kubernetes, Docker, and Helm • Improve system observability by implementing monitoring, logging, and alerting solutions • Troubleshoot infrastructure and production issues, performing root cause analysis and implementing long-term improvements • Collaborate closely with software engineers to integrate DevOps best practices throughout the development lifecycle • Optimize cloud infrastructure for performance, reliability, security, and cost efficiency • Leverage AI coding assistants to accelerate infrastructure development, automation, and operational troubleshooting

• Design, develop, and maintain scalable backend applications using modern Java (17/21) and the Spring ecosystem • Own software delivery from architecture and implementation through deployment, monitoring, and production support • Build and evolve microservices, RESTful APIs, and distributed systems with a focus on performance and reliability • Participate in solution design, technical decision-making, and architectural discussions across engineering teams • Diagnose production issues, optimize system performance, and implement robust long-term solutions • Collaborate closely with product and engineering stakeholders to challenge requirements and deliver high-quality outcomes • Mentor developers through code reviews, technical guidance, and knowledge sharing • Contribute to technical hiring and help strengthen engineering standards across the organization • Leverage AI coding assistants to improve development speed, code quality, and debugging workflows

• Define and execute the organization's long-term data strategy aligned with business objectives • Own the architecture and evolution of the enterprise data platform, covering ingestion, transformation, storage, and data access • Build, lead, and develop a high-performing data engineering team while establishing engineering standards and delivery best practices • Design and implement scalable data governance frameworks covering ownership, quality, lineage, metadata, and stewardship • Ensure the platform remains secure, reliable, scalable, and cost-efficient while supporting both operational and analytical workloads • Drive adoption of self-service analytics by enabling business teams to confidently access and leverage trusted data • Partner with senior leadership to identify strategic data initiatives and translate business priorities into technical roadmaps • Establish delivery processes, prioritization frameworks, and operating models that balance immediate business needs with long-term platform sustainability • Evaluate and implement appropriate tooling, cloud technologies, and vendor solutions where required • Champion a data-driven culture by improving data literacy, promoting best practices, and increasing organizational data maturity • Communicate technical strategy, delivery progress, risks, and business impact clearly to executive and non-technical stakeholders • Support the organization's AI and advanced analytics initiatives by building robust data foundations

• Design, develop, and maintain scalable backend applications using modern Java (17/21) and the Spring ecosystem • Own software delivery from architecture and implementation through deployment, monitoring, and production support • Build and evolve microservices, RESTful APIs, and distributed systems with a focus on performance and reliability • Participate in solution design, technical decision-making, and architectural discussions across engineering teams • Diagnose production issues, optimize system performance, and implement robust long-term solutions • Collaborate closely with product and engineering stakeholders to challenge requirements and deliver high-quality outcomes • Mentor developers through code reviews, technical guidance, and knowledge sharing • Contribute to technical hiring and help strengthen engineering standards across the organization • Leverage AI coding assistants to improve development speed, code quality, and debugging workflows