Responsible for designing, developing, and implementing AI-based solutions, including intelligent agents to automate processes and optimize operational workflows to drive business efficiency and improve client experience.
Responsibilities
Design and develop autonomous AI agents and multi-agent systems to automate complex business processes.
Create RAG (Retrieval-Augmented Generation) architectures integrating vector databases, business knowledge, and external APIs.
Implement client management agents connected via MCP to critical applications (CRM, media platforms, analytics, etc.).
Automate operational workflows in Google Marketing Platform (GMP), advertising platforms, and reporting tools.
Develop generative AI solutions to improve communications, insight generation, and repetitive tasks.
Requirements
University degree in Engineering
University degree in Data Science
University degree in Computer Science or similar
Master/specialization in Data Science, AI or Generative AI (valued)
Nice to have: Experience in media agency, digital marketing, or advertising environments
Consultant.e Data Engineer responsible for end‑to‑end data stack deployment, pipeline construction, data modeling, quality assurance and client support.
Responsibilities
Deploy a modern data stack end‑to‑end for clients
Build and maintain robust data pipelines
Model data for usability (SQL, data warehouse, datamarts)
Ensure data quality, reliability and monitoring
Support business teams in data understanding and usage
Own the technical side of client engagements from first demonstration through integration and production launch. This role blends hands-on engineering with solution architecture, delivering end-to-end software for external business users.
Compensation
Base salary: USD 170,000 to 205,000 per year
Responsibilities
Lead technical delivery for client accounts, covering demos, requirements discovery, design workshops, implementation and testing.
Design and build AI-driven agents and analytical products on top of shared internal platform components.
Connect the software to client systems such as CRMs and consumer apps, working with varied incoming data and building the pipelines to move it.
Partner with client technical and data staff over video to turn their existing processes into working production solutions.
Contribute field feedback to the core platform team, roughly 10-20% of your time, to help guide product direction.
Build and release live software that applies AI to engineering work, taking features from first requirements through testing to launch.
Compensation
Base salary: $185K to $205K
Responsibilities
Build end-to-end AI-driven workflows that convert technical documents into structured outputs that engineers can review.
Develop AI components that pull information out of technical papers, vendor sheets and engineering records, then organize it and draw conclusions from it.
Connect language model features with exact computational logic and the surrounding application stack.
Design test suites and evaluation methods that score accuracy, technical correctness, source traceability and practical value.
Turn specialist know-how into software components others can reuse.
