Cloud Data Engineer

Gilder Search Group; Los Angeles (CA); Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Long-term project

Compensation in USD

Paid time off

Job summary

Prediktive is seeking a Cloud Data Engineer based in Latin America to work on a long-term project for a Los Angeles–based Data Analytics and BI services company. You will help design and build the data store for autonomous agents and create scalable, multi‑modal data pipelines.

The role involves embedding data in vector and graph databases, developing RESTful APIs with Python (FastAPI/Django), and deploying data workloads on GCP.

Qualifications

• 5+ years of Data Engineering experience with production AI data systems.
• 5+ years Python experience with FastAPI, Pydantic, SQLAlchemy, and SQL.
• Hands-on with vector databases (Pinecone, ChromaDB) and building RAG pipelines.
• Experience with Airflow/Cloud Composer/Prefect and BigQuery.
• Experience on GCP or AWS and building scalable data services.

Responsibilities

• Design and build multi-modal data ingestion pipelines from relational databases and unstructured sources (PDFs, Word, diagrams).
• Develop embeddings in vector databases and graph databases to enable multi-step agent reasoning.
• Integrate autonomous coding agents into development workflows to plan, generate, and refactor data infrastructure and microservices.
• Collaborate with AI engineers to design evaluation pipelines and gold datasets for verification and quality scoring of AI outputs.
• Develop and maintain RESTful APIs using Python to expose structured and validated data.
• Deploy, monitor, and optimize data workloads on GCP using Vertex AI and BigQuery.

Skills

English

Data engineering

Python

Education

Bachelor’s degree in a relevant field

Tools

FastAPI

Django

SQLAlchemy

SQL

Pydantic

Airflow

BigQuery

Vertex AI

Pinecone

ChromaDB

Neo4j

Cloud Composer

Prefect

Job description

Prediktive -Latin America, LATAM, United States

We are looking for a Cloud Data Engineer based in Latin America to work on a long-term project for one of our clients, a Data Analytics and Business Intelligence services company based in Los Angeles.

The person in this role will be part of the new Product Engineering team tasked with designing and building the next generation of Agentic AI-powered products. This person will not just move data but will collaborate with the team to design the data store for our autonomous agents. The Engineer will be responsible for building multi-modal data pipelines that process structured and unstructured data into varied data stores, including vector and graph databases.

Responsibilities

• Design and build multi-modal data ingestion pipelines to collect and structure data from relational databases and unstructured sources such as PDFs, Word documents, and PNG/SVG diagrams.
• Develop and optimize the knowledge layer, managing embeddings in vector databases (e.g., Pinecone, ChromaDB, Vertex AI Search) and graph databases (e.g., Neo4j) to enable multi-step agent reasoning across distributed data sources.
• Integrate autonomous coding agents into daily development workflows to plan, generate, and refactor data infrastructure and microservices.
• Collaborate with AI Engineers to design and maintain evaluation pipelines and gold datasets used for automated verification, retrieval quality measurement, and confidence scoring of AI outputs.
• Develop and maintain scalable data services and RESTful APIs using Python (FastAPI/Django) to expose structured and validated data.
• Deploy, monitor, and optimize data workloads on GCP using services such as Vertex AI and BigQuery, ensuring system reliability, security, and cost efficiency.

Requirements

• Advanced Level of English.
• 5+ years of Data Engineering experience, with a proven track record of building production-grade AI data systems.
• 4+ years of experience working with Python and strong experience working with frameworks and libraries such as FastAPI, Pydantic, SQLAlchemy, and SQL for building scalable data services and microservices.
• Hands-on experience working with vector databases such as Pinecone or ChromaDB, and building RAG pipelines and GraphRAG patterns.
• Strong experience working with data orchestration and processing tools such as Apache Airflow, Cloud Composer, or Prefect, as well as BigQuery and DataProc.
• Hands-on experience working with cloud platforms such as GCP or AWS, deploying and managing scalable data pipelines and data workloads.
• Demonstrated experience using AI-assisted development tools such as GitHub Copilot, Cursor, Gemini Code Assist, Claude Code, Codex, or similar autonomous coding agents to accelerate software development workflows.
  

Bonus Points

• Bachelor’s Degree in Computer Science, Systems Engineering or related fields.

What we offer

• Long term positions.
• Compensation in USD.
• Paid time off.
• Cool clients and products.
• Work with great engineers.

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