As a Senior AI 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 you bring:
- 7+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership.
- 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
- 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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