🕒 February 25
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• Own end‑to‑end architecture and delivery of features for lift measurement products, from design and implementation through rollout and ongoing reliability. • Design, build, and optimize large‑scale data pipelines that power study setup, experiment execution, and results computation. • Drive AI enablement across the team by building the supporting tooling and processes (CI checks, test strategy, templates), coaching engineers, and ensuring adoption results in sustained improvements to delivery speed and system quality. • Translate measurement methodology into production systems: partner with Data Science to operationalize study design requirements into pipelines, services, tooling, and guardrails. • Build “rigor by default” mechanisms: automated data validation, randomization/holdout integrity checks, imbalance diagnostics, and continuous verification/backtesting. • Raise the bar on data quality and trust: define SLAs, build monitoring and anomaly detection, and lead root‑cause analysis for pipeline and study issues. • Mentor and up level engineers, driving strong technical execution and cross‑functional collaboration.
• BS+ in Computer Science (or related field) or equivalent practical experience. • 8+ years of professional software engineering experience, with a focus on data‑intensive systems. • Strong proficiency building and operating large‑scale data pipelines (batch and/or streaming) using Java/Scala/Kotlin or Python, plus SQL. • Experience designing reliable services and APIs, with solid foundations in distributed systems, data modeling, and performance optimization. • Demonstrated ability to transform a team’s engineering workflow using AI—from pilot to broad adoption—through tooling, enablement, and change leadership, with clear metrics (cycle time, defect rate, on-call load, incident rate). • Experience in AdTech and measurement products (e.g., conversion lift, brand lift) or adjacent experimentation/analytics platforms. • Working knowledge of experimentation and causal measurement fundamentals (randomization, holdouts, confounders, significance, power). • Practical experience with backtesting, controlled rollouts, and continuous verification for correctness in measurement/analytics systems. • Demonstrated ability to lead large cross‑functional initiatives, drive alignment, and deliver measurable impact through technical leadership.
• flexibility to do your best work • equity • health insurance
Apply Now🕒 February 25
11 - 50
Senior Infrastructure Engineer designing and building production infrastructure for Decagon. Collaborating with teams to ensure high-scale, low-latency systems and improving developer ergonomics.
🕒 February 25
11 - 50
Staff Software Engineer leading the architecture and design of Decagon's agent orchestration platform. Collaborating across teams to develop a reliable and intelligent AI solution.
🕒 February 24
10,000+ employees
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11 - 50
🤝 B2B
🤖 Artificial Intelligence
☁️ SaaS
Staff Software Engineer focusing on scaling AI-powered revenue platform for outbound efficiency. Collaborating with founders to establish engineering standards for growth.
🏢🏡 San Francisco – Hybrid
💵 $225k - $285k / year
⏰ Full Time
🔴 Lead
🧑💻 Full-stack Engineer
🦅 H1B Visa Sponsor
🕒 February 19
51 - 200
💸 Finance
💳 Fintech
☁️ SaaS
Senior Software Engineer at Modern Treasury designing AWS infrastructure and optimizing payment orchestration. Leading technical direction and contributing to payment rails strategy.
🏢🏡 San Francisco – Hybrid
💵 $200k - $260k / year
⏰ Full Time
🟠 Senior
🔴 Lead
🧑💻 Full-stack Engineer
🦅 H1B Visa Sponsor