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Principal Software Engineer

Designs and builds distributed systems, high-performance APIs, and data pipelines processing billions of events daily for real-time marketing platform. Leverages ML/LLMs for intelligent decision-making; requires 9+ years backend/data experience with Java/Go/Python, big data tools.

164k – 257kSan Francisco, CABackend EngineeringRemote9+ YOE

About the role

What You'll Do

  • Design and build distributed systems that process, enrich, and respond to billions of behavioral events per day in real time
  • Develop high-performance APIs and services that support advertising, identity, and intent features across the Marketing Platform
  • Leverage machine learning and large language models (LLMs) to analyze behavioral data, classify content, extract signals, and enable intelligent decision-making
  • Build intelligent agents using frameworks like LangGraph or MCP to reason over data and power user-facing insights
  • Design and operate data pipelines using tools like Kafka, Kinesis, and ClickHouse to support both streaming and batch workloads
  • Drive quality, performance, scalability, and observability across all systems you own
  • Collaborate cross-functionally with product managers, data scientists, and engineers to deliver customer-facing features and internal tooling
  • Contribute to technical leadership and mentorship of teammates

What You Bring

  • 9+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership
  • Distributed systems engineering (e.g., building low latency high throughput APIs, scalable microservices, event processing pipelines)
  • Big data infrastructure (e.g., streaming, warehousing, low-latency storage at scale)
  • Applied AI/ML, including use of LLMs for extraction, classification, or reasoning tasks
  • Proficiency in one or more core languages: Java, Go, Python
  • Solid grasp of SQL and large-scale data modeling
  • Familiarity with databases and tools such as: ClickHouse, DynamoDB, Bigtable, Memcached, Kafka, Kinesis, Firehose, Airflow, Snowflake
  • Comfortable using LLMs as part of your development workflow—whether via tools like Copilot, Cursor, ChatGPT, Claude, or others—to boost productivity, explore architecture ideas, and rapidly prototype
  • Skilled at designing and implementing LLM-powered systems such as RAG pipelines, agent frameworks (e.g., LangGraph), or intelligent workflows that reason across large datasets in real time

Bonus Points

  • Experience in ad tech, real-time bidding (RTB), or programmatic systems
  • Background in identity resolution, attribution, or behavioral analytics at scale
  • Contributions to open source in ML, infrastructure, or data tooling
  • Strong product instincts and a passion for building tools that drive meaningful outcomes

Skills

JavaGoPythonSQLKafkaKinesisClickHouseDynamoDBBigtableMemcachedAirflowSnowflakeLangGraphLLMsDistributed Systems

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