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SeniorRemoteUS

Data & AI Engineer

J
jobgether
Уровень
Senior
Формат
Remote
О роли

Описание вакансии

About the company

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.

Responsibilities

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

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.

Conditions

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.

Стек и навыки

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