Rosnet LLC

AI Data Engineer

Rosnet LLC · Parkville, Missouri, United States

IT Services and IT Consulting · 51-200 employees

8 h ago
Senior (5-10 yrs) Full-time United States
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About the role

Design and maintain scalable ETL pipelines and AI/ML workflows to power analytics products and operational intelligence. Collaborate cross-functionally to integrate LLM-based features and predictive analytics into the product and internal workflows.

What they look for

Python SQL Azure MLOps ETL Pipelines LLM RAG Databricks Apache Airflow Power BI Git Vector Databases Semantic Kernel LangChain Data Modeling CI/CD

Requirements

Requires 5-10 years of data engineering experience, including at least 2 years in AI/ML pipeline development or MLOps. A bachelor's degree in a technical field and proficiency in Python, SQL, and cloud data platforms are required.

Full description

Position Summary

Rosnet is looking for an experienced AI Data Engineer to sit at the intersection of data engineering, machine learning infrastructure, and AI-driven product development. In this role, you will design, build, and maintain scalable data pipelines and AI/ML workflows that power Rosnet’s analytics products and operational intelligence capabilities. You will collaborate closely with the Data, Product, and Engineering teams to deliver reliable, high-quality data solutions to embed AI capabilities directly into the product and internal workflows. This is an individual contributor role for someone who brings deep technical expertise and thrives in an environment where their work has direct, visible impact on the business and the clients we serve.

Key Responsibilities

  • Data Engineering & Pipeline Development
  • Design, build, and maintain robust ETL pipelines that ingest, transform, and serve data across Rosnet’s platform.
  • Develop and manage data models, schemas, and warehousing structures that support reporting and analytical workloads.
  • Ensure data quality, integrity, and observability through monitoring, testing, and documentation practices.
  • Optimize pipeline performance and cost efficiency across cloud-based data infrastructure.

AI & Machine Learning Integration

  • Build and operationalize AI/ML models and workflows, including LLM-based features, predictive analytics, and intelligent automation.
  • Develop and maintain MLOps infrastructure including model training pipelines, versioning, deployment, and monitoring.
  • Evaluate and integrate third-party AI tools and APIs (including LLMs and generative AI platforms) into data and product workflows.
  • Partner with Product and Engineering teams to translate business needs into AI-powered features and data products.

Collaboration & Technical Leadership

  • Work cross-functionally with Product, Engineering, and Client Services to define data requirements and deliver solutions.
  • Contribute to architectural decisions and technical standards within the Data team.
  • Document systems, pipelines, and processes clearly to support team knowledge-sharing and operational continuity.
  • Mentor and support junior data team members as the team grows.

Required Qualifications

Education

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field—or equivalent professional experience.

Experience

  • 5–10 years of professional experience in data engineering, with at least 2 years involving AI/ML pipeline development or MLOps.
  • Demonstrated experience building production-grade data pipelines and working in cloud-based data environments.
  • Experience in the SaaS industry strongly preferred; restaurant, hospitality, or foodservice industry experience is a plus.

Technical Skills

  • Proficiency in Python (or similar) for data engineering and ML model development.
  • Strong SQL skills including complex query writing, data modeling, and performance tuning.
  • Hands-on experience with cloud data platforms (Azure preferred; AWS or GCP considered).
  • Experience with Delta Lake / Parquet and medallion (Bronze–Silver–Gold) lakehouse design on platforms such as Microsoft Fabric or Databricks, including table optimization and maintenance.
  • Experience with data orchestration tools (e.g., Apache Airflow, Azure Data Factory, or similar).
  • Familiarity with vector databases, embedding pipelines, or Retrieval-Augmented Generation (RAG) architectures.
  • Experience with AI/ML frameworks and LLM tooling — e.g., scikit-learn and XGBoost/LightGBM for predictive ML (PyTorch/TensorFlow a plus); MLflow for experiment tracking and model management; Azure OpenAI and Anthropic Claude APIs; and agent/orchestration frameworks such as Semantic Kernel or LangChain (or equivalent).
  • Working knowledge of API integration and data ingestion from third-party platforms.
  • Familiarity with a BI and semantic-modeling platform (e.g., Power BI, Tableau, or Looker); hands-on knowledge of Power BI semantic modeling — DAX, TMDL, and XMLA endpoints — as an analytics serving layer is a strong plus.
  • Proficiency with version control and collaborative development workflows (e.g., Git); familiarity with CI/CD practices a plus.
  • Working knowledge of data governance, security, and PII/sensitive-data handling in a production environment.

Analytical & Functional Skills

  • Ability to translate ambiguous business problems into structured, scalable data solutions.
  • Strong debugging and troubleshooting skills across the full data stack.
  • Comfort working with large, complex, and sometimes messy datasets in a production environment.

Communication & Interpersonal Skills

  • Ability to communicate technical concepts clearly to non-technical stakeholders, including product managers and business leaders.
  • Collaborative working style with a strong sense of ownership and follow-through.
  • Comfortable operating with autonomy in a lean, fast-moving team environment.

Other Requirements

  • Must be authorized to work in the United States

Preferred Qualifications

  • Experience with real-time or streaming data pipelines (e.g., Kafka, Spark Streaming, or similar).
  • Exposure to AI-assisted development tooling (e.g., Claude Code, GitHub Copilot) and comfort using these tools in daily workflows.
  • Experience supporting multi-unit restaurant, retail, or franchise operators with data and analytics.
  • Relevant certifications in cloud platforms, data engineering, or AI/ML (e.g., Azure Data Engineer Associate, AWS Certified ML Specialty).

Competencies & Success Indicators

Technical Depth with Practical Impact

  • This role doesn’t just build technically sound solutions - they build things that work reliably in production and deliver measurable value to the business and our clients.
  • Pipelines are stable, well-documented, and require minimal reactive firefighting after launch.
  • AI/ML solutions deployed into production meet defined performance benchmarks and are monitored for drift.
  • Technical decisions are explained in terms of business impact, not just engineering merit.

Ownership Mindset

  • Takes full responsibility for the solutions they build, from design through delivery and ongoing operational health.
  • Proactively identifies data quality issues and proposes solutions before they surface downstream.
  • Sees work through to completion—not just to “ship,” but to adoption and operational stability.
  • Surfaces architectural improvements or technical debt without waiting to be asked.

Collaborative Engineering

  • Works effectively across technical and non-technical teams to deliver shared outcomes.
  • Translates data concepts into plain language for Product, CS, and leadership audiences.
  • Actively participates in technical planning, retrospectives, and cross-team discussions.
  • Shares knowledge generously and contributes to a culture of continuous learning.

AI Curiosity & Adaptability

  • Stays current with the fast-moving AI/ML landscape and applies emerging capabilities thoughtfully.
  • Regularly evaluates new AI tools and frameworks for potential application at Rosnet.
  • Comfortable experimenting, iterating, and failing fast in pursuit of better solutions.
  • Applies AI-assisted development tools to increase personal and team productivity.

Work Environment & Physical Requirements

  • This position is primarily performed in an office-based environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the role in accordance with the Americans with Disabilities Act (ADA) and applicable state laws.
  • Primarily sedentary role with extended periods of computer use.
  • Hybrid work model; expected to work from the Kansas City office on a regular cadence as defined by department leadership.
  • Ability to attend virtual and in-person meetings as required, including occasional cross-functional or company-wide gatherings.

Compliance & Equal Opportunity Statement

  • Rosnet is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, or any other characteristic protected by applicable federal, state, or local law.
  • This job description is not intended to be a comprehensive list of all duties, responsibilities, or qualifications. Management reserves the right to modify, add, or remove duties as business needs change. This document does not constitute an employment contract.
  • Rosnet participates in E-Verify.