53m ago

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Data & AI Engineer

United StatesRemoteFull-timemid

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

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.

Requirements Summary

At least 5 years of experience building and deploying production applications, particularly data-intensive systems and backend services.

Technical Tools

Machine Learning EngineerData

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.

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

~2 min read

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.

What We Offer

~2 min read

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.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

✓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.