As a Principal Engineer on our Advertising, Company Intelligence, and Intent team, you’ll help design and implement the core systems that power our real-time marketing platform. From high-throughput ad infrastructure to large-scale identity resolution and intelligent systems enhanced by LLMs, push the boundaries of scale, intelligence, and speed—and deliver real-world business impact.

You’ll be joining a team with a broad range of ambitious, technically deep projects—from APIs that process tens of billions of events per day, to new buyer intent algorithms powered by LLMs, to a unified B2B identity graph. Depending on your strengths and interests, you’ll be matched to the initiatives where you can have the greatest impact.

This is a high-growth, high-ownership environment operating at the edge of what’s possible in modern software engineering, data infrastructure, and applied AI.

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 We’re Looking For

• 8+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership.
  
  
• Strong experience in at least one of the following:
• Distributed systems engineering (e.g., building low latency high and 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

AI-Native Development Mindset

• 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

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