Senior Data Engineer (m/f/d)

eigenblue • New York, NY

5d • Remote

About The Position

eigenblue is building intelligent engineering systems by combining human expertise with proprietary AI models that generate system architectures across software, electronics, mechanics, and applied physics. The Senior Data Engineer will build the data infrastructure for eigenblue’s AI product from the ground up, architecting and implementing scalable data platforms and advanced retrieval-augmented generation (RAG) pipelines that power proprietary AI systems and reasoning models. The role works closely with AI engineers and cross-functional teams to develop and bring advanced reasoning models and AI features into user-facing products.

The position also contributes to data and analytics platforms, data quality assurance and ingestion, dashboards and analytics, and engineering best practices. It involves collaborating with AI Engineers, Product Managers, Chief Officers, and Software Teams in an early-stage product environment.

This is a remote position. The package includes an annual base salary range of $100,000–$250,000, based on experience, skills, and location. Benefits include medical, dental, and vision insurance, access to OpenUp, optional voluntary benefits, a 401(k) plan with company match based on level, an annual performance and progression review with potential performance-based adjustments, an individual learning and development budget, generous PTO, WeWork day-pass access, and a travel budget for visits to the Munich headquarters and company events.

Requirements

• University degree in Computer Science, Software Engineering, Data Science/Engineering, or a related discipline.
• At least 4 years of experience in agile development projects.
• Experience with data engineering for production ML/AI deployment or MLOps using cloud platforms such as Azure, AWS, and/or GCP.
• Experience designing data platform and data processing pipeline architectures, and building batch and real-time streaming solutions using technologies such as PySpark or Kafka.
• Experience with data warehousing services such as AWS Redshift or Snowflake, LLM data stores, SQL/no-SQL tools, and data management processes.
• Strong analytical and problem-solving skills, and comfort with ambiguity and rapid changes common in early-stage product development.
• Excellent verbal and written English communication skills, with the ability to collaborate effectively across multidisciplinary teams.

Nice To Haves

• Expertise with AI tools and LLM providers.
• Experience implementing advanced RAG pipelines, such as GraphRAG.
• Experience with agents/MCP and multi-agent architectures.
• Experience with ML model training, LLM fine-tuning, RLHF, or LLM-as-a-judge metrics.
• Experience working in a multidisciplinary environment on customer-facing products and research projects.

Responsibilities

• Build scalable data and analytics platforms, including data stores, warehouses, and RAG pipelines for AI systems and reasoning models.
• Work with AI Engineers to design, implement, and test ideas for advanced AI reasoning using the company’s proprietary ontology and algorithms alongside public tools and data.
• Create data visualizations using dashboarding and analytics solutions.
• Mentor other engineers on data engineering best practices and help ensure high-quality customer solutions.
• Improve quality assurance and data ingestion approaches by introducing tools and frameworks.
• Collaborate with AI Engineers, Product Managers, Chief Officers, and Software Teams to integrate AI features into user-facing products.

Benefits

• Medical, dental, and vision insurance.
• Access to mental health partner OpenUp.
• Option of additional voluntary benefits.
• 401(k) plan with company match based on level.
• Annual performance and progression review, with performance-based package adjustments.
• Individual learning and development budget.
• Generous PTO policy.
• WeWork day-pass access.
• Travel budget for visits to the Munich headquarters and company events.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior