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!