Principal Software Engineer

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.

$163,800—$257,400 USD

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