Client-Facing Field Engineer: AI, Data & Integrations

Addepar, Inc.; Salt Lake City (UT); On-site; USD 95,000 - 149,000; Full time

Job summary

Addepar, Inc. is seeking a Field Engineer who will embed directly with clients to architect and build mission-critical integrations, automations, and data solutions across its platform, including ADX (Databricks) and AI-driven tooling.

Ideal candidates have 3+ years in software or data engineering, strong Python production-grade API and data-pipeline skills, and experience with large-scale data processing in financial contexts.

Qualifications

• 3+ years of software or data engineering, with forward-deployed experience.
• Strong Python production-grade app and API development.
• Experience with Databricks, Spark, and large-scale data processing.
• Understanding of financial data domains like portfolio management.

Responsibilities

• Deploy client-ready integrations and data pipelines at client sites.
• Design production-grade solutions to accelerate onboarding and scale.
• Develop AI-driven automation to transform data and validation.
• Own ADX implementations and Databricks data infrastructure.
• Translate client requirements into scalable technical solutions.
• Write production Python code for ETL and data tooling.
• Lead technical workstreams end-to-end and ensure client success.
• Collaborate with product, engineering, and services to roadmap.
• Develop internal tools and best practices for faster delivery.
• Set clear technical expectations with stakeholders.

Skills

Python

REST APIs

SQL

AI/ML concepts

Git

Tools

Databricks

Spark

CI/CD

APIs

Job description

Addepar, Inc. is seeking a Field Engineer who will embed directly with clients to architect and build mission-critical integrations, automations, and data solutions across its platform, including ADX (Databricks) and AI-driven tooling.

Ideal candidates have 3+ years in software or data engineering, strong Python production-grade API and data-pipeline skills, and experience with large-scale data processing in financial contexts.