Engineering Manager

Engineering Manager ABOUT THE ROLE This is a pivot-point role for a leader who is ready to move beyond traditional software management and lead a team into the era of AI-Native Engineering and ML-Driven Growth. The GDP pod is the engine room of Hinge Health's growth strategy. You own the data pipelines, event streams, and the emerging "Intelligence Layer" that powers every member interaction—from the first ad they see to the "Daily Streak" notification that keeps them pain-free. In 2026, your mission is to transform GDP from a data mover to a decision engine. You will partner with Data Science to operationalize high-value ML models (like our Direct Mail Propensity Model and Contextual Bandits) that autonomously decide the channel, content, and timing of our marketing. Simultaneously, you will pioneer our "Harness Engineering" initiative, transforming your pod's workflow from manual coding to managing autonomous AI agents that build, test, and verify our data infrastructure. You will lead a high-performing team in Bangalore, serving as the strategic bridge between SF Product Strategy and technical execution. WHAT YOU’LL ACCOMPLISH - Build the "Intelligence Layer": Move beyond simple data piping. Architect the real-time decisioning layer that ingests ML signals (e.g., Churn Risk, Propensity to Convert) and routes them instantly to execution platforms like Iterable. - Operationalize Growth ML Models: Partner with Data Science to take predictive models out of the lab and into production. You will own "Phase 3" of the model lifecycle: hardening, serving, and monitoring models that control millions of dollars in marketing spend. - Lead the Transition to Harness Engineering: Drive the adoption of AI-native workflows (using tools like Cursor and Claude Code). Shift the team’s focus from "typing code" to building the test harnesses, specs, and safety rails that allow agents to autonomously maintain our pipelines. - Guarantee Data Trust ("Glass Box" Observability): Champion a culture of radical observability. Implement automated "data sentinels" and contract tests that catch schema violations and freshness issues before they impact our marketing campaigns. BASIC QUALIFICATIONS - 2+ years of experience managing engineering teams. You are a "player-coach" who can build a "One Team" culture, bridging the gap between SF and Bangalore with high-agency leadership. - 3+ years of experience with data engineering technologies including experience with distributed data processing frameworks (e.g., PySpark, Databricks) and SQL. - Experience with production data pipelines and understanding of data lifecycle management, including pipeline orchestration, monitoring, and operational excellence practices. PREFERRED QUALIFICATIONS - ML Ops & Model Serving Experience: You understand the lifecycle of data and models. You have experience with Kafka and event-driven architectures, and you know what it takes to serve an ML model in production (latency, feature stores, drift monitoring). - AI-Forward Leadership: You are excited, not intimidated, by the shift to AI-assisted engineering. You are eager to experiment with new workflows where engineers act as architects and auditors of AI-generated code. - Architectural Rigor: You can simplify complex systems. You have a track record of converging "sprawling" pipeline patterns into robust standards (e.g., moving ad-hoc scripts into a unified Event-Driven Architecture). - Operational Excellence: You value SLOs, runbooks, and incident management. You believe that "production reliability" is a feature, especially when dealing with data that drives real-time member health decisions. - Experience with Marketing Tech (Iterable, Braze) or Customer Data Platforms (Segment, Hightouch). - Experience implementing Contextual Bandits or similar experimentation frameworks. - Background in Healthcare/HIPAA compliant environments. ABOUT HINGE HEALTH Hinge Health is moving people beyond pain by transforming ... (truncated, view full listing at source)