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Engineering Manager - Runtime Team (India or US) - Remote Ok at Nexla. . Location: Remote. About Nexla. . Nexla is an innovative enterprise-grade data integration platform that empowers businesses to create AI-ready data products and deliver enterprise-grade AI without coding, up to 10x faster than alternatives. Built on a Data Fabric architecture, our platform brings together multi-speed data integration, data preparation, monitoring, and governance into a unified no-code/low-code interface. Trusted by leading companies including DoorDash, LinkedIn, Johnson & Johnson, and AutoDesk, we're at the forefront of AI-powered data operations.. . Position Overview. . As . Engineering Manager for the Runtime Team. at Nexla, you will lead the engineering organization responsible for the core execution engines that power our data integration platform. You'll manage a team of Engineers working on distributed systems that process massive data volumes in real-time using technologies like Kafka, our proprietary execution engine, Ray for AI data processing, and other cutting-edge distributed computing frameworks. This role requires technical depth combined with strong leadership skills to guide high-performing engineers while establishing processes that enable teams to operate at maximum velocity.. . Key Responsibilities. . Technical Leadership & Architecture. . . Partner with Senior/Principal Engineers to architect scalable, fault-tolerant distributed systems capable of handling enterprise-scale data workloads. . Drive technical decisions around stream processing architectures, distributed computing frameworks, and real-time data pipeline optimization. . Establish technical standards and best practices for building mission-critical, highly available distributed systems. . . Team Leadership & People Management. . . Manage and mentor a team of Senior and Principal Engineers, providing technical guidance while fostering professional growth and career development. . Lead hiring efforts to attract top-tier distributed systems talent and build a world-class runtime engineering team. . Conduct performance reviews, set engineering goals, and create development plans that align individual growth with business objectives. . Foster a culture of technical excellence, innovation, and collaborative problem-solving within the team. . . Process Excellence & Velocity. . . Design and implement engineering processes that enable high-velocity development without compromising system reliability or code quality. . Establish DevOps practices, CI/CD pipelines, and deployment strategies for distributed systems operating at scale. . Implement monitoring, alerting, and observability frameworks to ensure system health and rapid incident response. . Drive adoption of agile methodologies, sprint planning, and technical project management practices optimized for distributed systems development. . . Cross-Functional Collaboration. . . Collaborate closely with Product, and AI teams to align runtime capabilities with business requirements and customer needs. . Partner with DevOps teams to ensure seamless deployment, scaling, and operational excellence of runtime systems. . Work with the Solution and Customer Engineering teams to optimize data processing workflows and integrate new AI capabilities. . Communicate technical roadmaps, system capabilities, and engineering priorities to executive leadership and stakeholders. . . System Operations & Scalability. . . Oversee the operational excellence of production runtime systems, ensuring 99.9%+ uptime.. . Lead capacity planning, performance optimization, and cost management initiatives for large-scale data processing infrastructure. . Drive incident response, post-mortem analysis, and continuous improvement processes to enhance system reliability. . Ensure comprehensive disaster recovery, data consistency, and security practices across all runtime systems. . .  . . Required Qualifications. . Leadership & Management Experience. . . 5+ years. of engineering management experience leading senior engineering teams in distributed systems or data infrastructure. . 2+ years. managing Senior/Principal Engineers and technical leads in high-growth technology companies. . Proven track record of building and scaling high-performing engineering teams (10+ engineers). . Experience establishing engineering processes, best practices, and development methodologies that drive velocity and quality. . . Technical Expertise. . . 5+ years. of hands-on engineering experience in distributed systems, stream processing, or large-scale data infrastructure. . Deep expertise with . Apache Kafka. ecosystem including Kafka Streams, Connect, and distributed event streaming architectures. . Experience with . Ray. or similar distributed computing frameworks (Spark, Flink, Dask) for AI/ML data processing workloads. . Strong background in building and operating mission-critical production systems at enterprise scale. . . Distributed Systems & DevOps. . . Expert-level understanding of distributed systems concepts: consensus algorithms, fault tolerance, partitioning, replication, and consistency models. . Extensive experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker). . Deep knowledge of DevOps practices including Infrastructure as Code, CI/CD pipelines, monitoring, and observability tools. . Experience with database technologies, data warehouses, and real-time analytics systems. . . Large-Scale Data Processing. . . Proven experience building systems that process terabytes of data daily with sub-second latency requirements. . Understanding of data serialization formats, compression techniques, and optimization strategies for high-throughput data pipelines. . Experience with stream processing patterns, event-driven architectures, and real-time data transformation systems. . Knowledge of data governance, security, and compliance requirements for enterprise data platforms. . . Preferred Qualifications. . . Experience at high-growth startups or technology companies in data infrastructure, platform engineering, or distributed systems. . Experience with multi-tenant, enterprise-grade SaaS platforms serving Fortune 500 customers. . Experience with performance engineering, capacity planning, and cost optimization at scale. . Knowledge of data privacy regulations (GDPR, CCPA) and enterprise security frameworks. . . Team & Technology Context. . Team Composition. . . Manage 8-12 Senior and Principal Engineers with deep expertise in distributed systems. . Collaborate with specialists in AI/ML, DevOps, Platform Engineering, and Data Engineering. . . Technology Stack. . . Stream Processing:. Apache Kafka, Kafka Streams, Kafka Connect, custom event streaming solutions. . Distributed Computing:. Ray, Apache Spark, custom proprietary execution engines. . Infrastructure:. Kubernetes, Docker, AWS/GCP, Terraform, service mesh technologies. . Data Systems:. Multiple database technologies, data warehouses, real-time analytics engines. . Languages:. Primarily Java and Python. . . Scale & Performance Requirements. . . Process billions of events per day with sub-second end-to-end latency. . Support enterprise customers with strict SLA requirements (99.9%+ uptime). . Handle dynamic scaling from hundreds to millions of data transformations per minute. . Maintain data consistency and fault tolerance across geographically distributed systems. . . Why Nexla. . Technical Impact. . . Lead engineering for the core runtime systems that power enterprise data operations for Fortune 500 companies. . Build next-generation distributed systems that democratize access to real-time data processing and AI capabilities. . Work on cutting-edge problems in stream processing, distributed computing, and AI-powered data transformation. . . Leadership Growth. . . Opportunity to build and scale a world-class engineering organization in a high-growth environment. . Direct impact on technical strategy and product direction at a fast-growing data infrastructure company. . Mentorship from experienced technology leaders and exposure to executive-level strategic decision making. . . Culture & Environment. . . Collaborative, engineering-driven culture that values technical excellence and innovation. . Remote-first organization with flexible working arrangements and strong emphasis on work-life balance. . Competitive compensation package including equity, comprehensive benefits, and professional development opportunities. . Investment in cutting-edge tools, technologies, and continuous learning initiatives. . . Ready to lead the future of distributed data processing?. Join us in building the runtime systems that power enterprise AI and data operations at global scale. . Apply today to join the Nexla team!