Adobe Systems

3 months ago

Senior AI Platform Engineer- Data and Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Design and build streaming-first data pipelines and lakehouse infrastructure to enable real-time AI, analytics, and autonomous agents at scale. Own the ML Attribute Store, build MCP-compatible Agent Data APIs, and develop agentic, self-healing pipelines while optimizing observability and cost. Collaborate across Data Science, Engineering Operations, Product, and Experimentation to reduce engineering toil and accelerate velocity.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design and build streaming-first data pipelines that collapse end-to-end latency from hours to minutes, through event-driven architectures.
•Own and extend the ML Attribute Store — building low-latency online serving capabilities alongside batch feature computation with unified batch/streaming aggregation to prevent training-serving skew.
•Build MCP-compatible Agent Data APIs and tool servers that make the lakehouse discoverable and queryable by autonomous AI agents through standardized protocols, semantic layers, and catalog-driven data discovery.
•Develop agentic framework — automated anomaly detection, duplicate event cleanup, transient event lifecycle management with audit trails, pipeline self-healing, and root cause analysis automation.
•Drive operational excellence: observability, incident detection and response automation, performance tuning, cost optimization, and on-call ownership for mission-critical platform services.

Pay and Benefits

Salary: USD 159,200 - 301,600 annually

Key Requirements

•6+ years of experience in data platform engineering, distributed systems, or backend infrastructure at scale.
•Deep hands-on experience with Apache Spark, Databricks, Delta Lake, or equivalent lakehouse technologies (Iceberg, Hudi).
•Proven track record building and operating large-scale pipelines processing billions of events daily with sub-hour latency SLAs.
•Strong experience with streaming systems: Kafka, Kinesis, Flink, Spark Structured Streaming, or Delta Live Tables.
•Proficiency in Python and/or Scala; SQL fluency required. Java or Go is a plus.

Experience:6+ yearsData platformDistributed systemsLakehouseStreaming

Skills:PythonScalaSQLJavaGoDockerKubernetesSparkDatabricksKafkaAWSAzure

Tech Stack:Apache SparkDatabricksDelta LakeIcebergHudiKafkaKinesisFlinkSpark Structured StreamingDelta Live TablesPythonScalaSQLJavaGoAWSAzureDockerKubernetes

Company Brief

Adobe Systems

Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor

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Adobe Systems

3 months ago

Senior AI Platform Engineer- Data and Systems

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design and build streaming-first data pipelines that collapse end-to-end latency from hours to minutes, through event-driven architectures.
•Own and extend the ML Attribute Store — building low-latency online serving capabilities alongside batch feature computation with unified batch/streaming aggregation to prevent training-serving skew.
•Build MCP-compatible Agent Data APIs and tool servers that make the lakehouse discoverable and queryable by autonomous AI agents through standardized protocols, semantic layers, and catalog-driven data discovery.
•Develop agentic framework — automated anomaly detection, duplicate event cleanup, transient event lifecycle management with audit trails, pipeline self-healing, and root cause analysis automation.
•Drive operational excellence: observability, incident detection and response automation, performance tuning, cost optimization, and on-call ownership for mission-critical platform services.

Pay and Benefits

Salary: USD 159,200 - 301,600 annually

Key Requirements

•6+ years of experience in data platform engineering, distributed systems, or backend infrastructure at scale.
•Deep hands-on experience with Apache Spark, Databricks, Delta Lake, or equivalent lakehouse technologies (Iceberg, Hudi).
•Proven track record building and operating large-scale pipelines processing billions of events daily with sub-hour latency SLAs.
•Strong experience with streaming systems: Kafka, Kinesis, Flink, Spark Structured Streaming, or Delta Live Tables.
•Proficiency in Python and/or Scala; SQL fluency required. Java or Go is a plus.

Experience:6+ yearsData platformDistributed systemsLakehouseStreaming

Skills:PythonScalaSQLJavaGoDockerKubernetesSparkDatabricksKafkaAWSAzure

Tech Stack:Apache SparkDatabricksDelta LakeIcebergHudiKafkaKinesisFlinkSpark Structured StreamingDelta Live TablesPythonScalaSQLJavaGoAWSAzureDockerKubernetes

Company Brief

Adobe Systems

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor