Senior Data Science Engineer, GenAI Platforms, Data Infrastructure

Adobe

Senior Data Science Engineer building practical AI and data systems for Adobe. Focusing on GenAI agents, data pipelines, and customer intelligence products in a hands-on engineering role.

Posted 4/28/2026full-timeSan Francisco • California, Texas, Washington • 🇺🇸 United StatesSenior💰 $133,100 - $236,400 per yearWebsite

Tech Stack

Tools & technologies

CloudPythonSparkSQL

About the role

Key responsibilities & impact

Build production data pipelines, feature workflows, and platform services using Python, SQL, Spark, Databricks, Delta Lake, APIs, and cloud tools.
Create LLM-powered agents and AI workflows that summarize customer signals, generate insights, recommend actions, and reduce manual work.
Own platform components such as data ingestion, orchestration, semantic layers, tool integrations, access patterns, monitoring, and reliability.
Combine structured and unstructured data from usage, adoption, support, success, value, account, and operational systems.
Improve GenAI quality through evaluation, retrieval design, prompt and tool design, feedback loops, and production monitoring.
Strengthen data quality, lineage, alerting, access control, governance, and operational support.
Partner with product, engineering, data science, business operations, and customer-facing teams to turn priority problems into working systems.
Apply strong engineering practices through Git, code review, CI/CD, Databricks Repos, documentation, and reproducible development.

Requirements

What you’ll need

8+ years in data engineering, machine learning engineering, data science engineering, analytics engineering, platform engineering, or a related technical role.
Production work with Python, SQL, Spark, Databricks, Delta Lake, distributed data processing, and workflow orchestration.
Hands-on work with GenAI or LLM systems, including agents, copilots, retrieval-augmented generation, semantic search, tool/function calling, prompt workflows, or AI automation.
Strong knowledge of data modeling, data quality, lineage, access control, observability, and scalable pipeline design.
Ability to guide work from discovery through architecture, development, deployment, monitoring, adoption, and iteration.
Good judgment on when to prototype, when to harden for production, and how to manage technical debt.
Clear communication with technical teams, business stakeholders, and senior leaders.
Ability to work independently, navigate ambiguity, prioritize high-impact work, and deliver in a fast-moving environment.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience.

Benefits

Comp & perks

comprehensive benefits programs

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonSQLSparkDatabricksDelta Lakedata modelingdata qualityworkflow orchestrationGenAILLM systems

Soft Skills

clear communicationindependent worknavigating ambiguityprioritizationjudgmentguiding workcollaborationproblem-solvingiterationfast-paced delivery

Certifications

Bachelor’s degreeMaster’s degree