Job Opportunities API

Our mission is to transform how people and machines work together to push the boundaries of human productivity. A leader in Industrial AI, Augury helps the world’s manufacturers leverage real-time production insights to drive new levels of efficiency. Combining predictive and prescriptive AI technology with industry expertise, production teams can proactively address alerts, minimize downtime, reduce asset costs, and maximize yield and capacity. Our customers achieve payback in six months or less, enabling global scale. We're looking for team members excited to partner with the world's manufacturers and build the future of production together. Our Data Intelligence Hub (DIH) is building the next-generation Industrial Data Intelligence platform: a contextual layer that connects machine health, operational, maintenance, engineering, and enterprise data on top of a site Digital Twin backbone. This foundation powers agentic, AI-native experiences that help users explore their sites, answer complex questions, and make better decisions in one place. You will lead the Data Platform team within DIH, responsible for building robust, scalable data services and pipelines that power our products, digital twins, and AI agents. This is a hands-on engineering leadership role. You are first and foremost a strong software engineer with deep experience in data-intensive systems—not a traditional ETL/BI data engineer. You will build and lead a new Data Platform team in India, setting the technical bar for production-grade systems with strong standards for software design, reliability, scalability, and testing. A Day In Your Life Lead and grow a team of ~5 Software Engineers in India, providing technical direction, coaching, and hands-on contribution (~30–50%). Own the technical vision and roadmap for DIH’s data platform in India, in close partnership with DIH leadership in Israel. Design and evolve scalable, data-centric backend services and pipelines that support Digital Twin and AI/agentic use cases. Set a high engineering bar for the team: clean code, testing, observability, and strong ownership culture. Technical Leadership & Architecture Own the architecture and long-term evolution of DIH data services and pipelines built in India. Define and enforce data modeling standards (raw / modeled / aggregate layers, e.g., Bronze/Silver/Gold) across DIH systems. Make key architectural decisions across storage, lakehouse, and streaming systems (e.g., Databricks, Kafka), including trade-offs in cost, latency, and correctness. Lead design reviews and guide engineers through complex distributed systems and data pipeline decisions. Production Data Systems Build end-to-end data pipelines from raw industrial events to validated, modeled, and aggregated datasets powering products and AI agents. Ensure pipelines are incremental, idempotent, and resilient to duplicates, late events, and schema changes. Design time-based aggregations and event-time correctness (watermarks, backfills, reprocessing). Model key industrial relationships (machines, sensors, factories, work orders, tenants) to support analytics and AI/graph-style queries. Ensure systems are observable and reliable in production (metrics, logging, tracing, data quality checks). Streaming, Scale & Reliability Build systems that scale to high-volume industrial data workloads (hundreds of TB, millions of events/hour). Design streaming and event-driven systems with proper consumer patterns (idempotency, replay, lag monitoring). Make pragmatic trade-offs across partitioning, MERGE vs append-only, backfills, and cost vs performance. Ensure multi-tenant isolation and correctness across schemas, keys, and access patterns. AI-Native & Cross-Functional Collaboration Partner with DIH and AI/ML teams to make data models and pipelines agent-ready (structured schemas, deterministic outputs, tool-friendly queries).