Data & AI Engineer

Job description

**This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data & AI Engineer based in the United States.** As a Data & AI Engineer, you will build and scale the data infrastructure and AI capabilities behind an innovative, AI-powered creative intelligence platform. You will connect creator data, advertising performance, engagement metrics, and commerce insights to help teams make smarter, data-driven decisions. Your responsibilities will span data architecture, backend engineering, LLM integrations, semantic search, and full-stack product development. Working with modern technologies such as Python, Django, PostgreSQL, and leading AI models, you will transform complex datasets into actionable intelligence. This hands-on role offers significant technical ownership, autonomy, and the opportunity to shape an emerging product from the ground up. You will collaborate closely with product and creative teams in a remote-first environment focused on experimentation, scalability, and measurable business impact. ### Accountabilities - **Data Architecture and Engineering:** Design, build, and maintain scalable data pipelines that integrate advertising performance, sales, engagement, and creator data from platforms such as TikTok, Meta, and other digital channels. - **Backend Development:** Develop robust data models, databases, and backend services using Python, Django, PostgreSQL, and SQL to support reliable data processing and platform functionality. - **API Integrations:** Connect third-party platforms and services, managing authentication, rate limits, complex data structures, and asynchronous workflows to ensure efficient and dependable data ingestion. - **AI and Machine Learning Integration:** Build and maintain LLM-powered workflows for video analysis, creative tagging, content classification, and AI-generated insights using models and services such as Gemini and Claude. - **Semantic Search and Data Intelligence:** Develop search and retrieval capabilities that transform large volumes of structured and unstructured data into relevant, actionable creative insights. - **AI Performance Optimization:** Improve the accuracy, reliability, scalability, and cost efficiency of AI-powered systems through effective prompt engineering, structured outputs, and continuous evaluation. - **Product and Full-Stack Development:** Build end-to-end features, including dashboards, search interfaces, content libraries, and reporting tools that connect creative performance with creator history and engagement data. - **Cross-Functional Collaboration:** Partner with product and creative teams to translate business needs into practical, scalable technical solutions that support better creative and commercial decisions. - **Technical Ownership:** Lead engineering initiatives from architecture and implementation through deployment, monitoring, troubleshooting, and optimization. - **Continuous Improvement:** Use AI-assisted development tools to accelerate coding, testing, and delivery while contributing to engineering standards, architectural decisions, and platform improvements as the product grows. ## Requirements - **Professional Experience:** At least 5 years of experience building and deploying production applications, particularly data-intensive systems and backend services. - **Programming and Backend Expertise:** Advanced proficiency in Python, Django, PostgreSQL, and SQL, with the ability to design reliable, maintainable, and scalable applications. - **Data Engineering:** Proven experience designing scalable data models, data pipelines, and asynchronous processing systems using Celery, Redis, or comparable technologies. - **LLM Integration:** Hands-on experience integrating large language model APIs into production environments, including prompt engineering, structured outputs, performance evaluation, and cost management. - **Third-Party API Management:** Strong experience integrating external APIs and handling authentication, rate limits, asynchronous operations, and complex data formats. - **AI-Assisted Development:** Proficiency with AI-powered coding tools such as Claude Code or similar platforms to improve development speed, testing, and implementation quality. - **Full-Stack Capabilities:** Ability to independently design, develop, and deploy end-to-end product features across backend services and frontend components. - **Technical Problem-Solving:** Strong analytical skills and the ability to troubleshoot complex engineering challenges, evaluate trade-offs, and make sound technical decisions independently. - **Communication and Collaboration:** Excellent communication skills, a collaborative mindset, and the ability to work effectively with cross-functional teams in a remote environment. - **Ownership and Adaptability:** A proactive, resourceful approach to engineering, with a willingness to take ownership, experiment with emerging technologies, and deliver practical solutions in a changing environment. - **Nice to Have:** Experience with retrieval-augmented generation (RAG), pgvector, AI agents, video processing, AWS, advertising technology, or creator-economy platforms. - **Technology Environment:** Familiarity with or willingness to work across a modern technology stack that includes Python, Django, PostgreSQL, Celery, Redis, HTMX, Tailwind CSS, Gemini, Claude, Docker, AWS, and GitHub Actions. ## Benefits - **Competitive Compensation:** Competitive salary with eligibility for a performance-based bonus. - **Comprehensive Healthcare:** Health, dental, and vision insurance coverage. - **Flexible Time Off:** Flexible paid time off (PTO) to support work-life balance. - **Remote-First Work Environment:** The flexibility to work remotely from within the United States, with periodic team gatherings. - **Professional Networking:** Access to an industry-leading network of professionals across social commerce, creator partnerships, and brand marketing. - **Technical Ownership and Growth:** The opportunity to shape an emerging AI-powered product, influence technical architecture, and work with modern data engineering and AI technologies. - **Collaborative Culture:** An environment that values autonomy, experimentation, continuous learning, and meaningful contributions. - **Inclusive Workplace:** A commitment to equal opportunity, diversity, and an inclusive culture where employees are valued and empowered.