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Lead Engineer at Weekday AI. This role is for one of the Weekday's clients. Min Experience: 10 years. Location: USA. JobType: full-time. As a Lead Engineer, you will play a pivotal role in architecting and delivering complex stream-processing solutions, mentoring engineering teams, and collaborating closely with cross-functional stakeholders to translate business requirements into robust technical systems.. Key Responsibilities. Lead the architecture, design, and implementation of real-time data processing pipelines using . Apache Flink. . . Develop and maintain high-performance backend services and distributed systems using . Java. . . Design scalable event-driven architectures capable of handling high-throughput and low-latency workloads. . Optimize streaming jobs for performance, fault tolerance, and resource efficiency. . Ensure best practices in code quality, testing, observability, and CI/CD processes. . Collaborate with data engineering, DevOps, and product teams to define technical roadmaps and system requirements. . Conduct design reviews, troubleshoot production issues, and implement long-term reliability improvements. . Mentor and guide engineers, fostering a culture of technical excellence and continuous improvement. . Contribute to infrastructure decisions related to distributed processing, cloud deployment, and containerized environments. . Required Skills & Qualifications. 10–12 years of overall experience in software engineering, with significant exposure to distributed systems. . Strong hands-on expertise in . Apache Flink. , including stream processing concepts such as windowing, state management, checkpoints, and event-time processing. . Advanced proficiency in . Java. , including concurrency, multithreading, memory management, and performance tuning. . Deep understanding of data streaming architectures and real-time processing frameworks. . Experience working with messaging systems (e.g., Kafka or similar platforms). . Strong knowledge of data structures, algorithms, and system design principles. . Experience deploying and managing applications in cloud environments (AWS, Azure, or GCP). . Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes. . Solid understanding of CI/CD pipelines, automated testing frameworks, and monitoring tools. . Experience with SQL and NoSQL databases in high-scale environments. . Leadership & Soft Skills. Proven experience leading engineering teams or owning major technical initiatives. . Strong architectural decision-making abilities with a focus on scalability and maintainability. . Excellent problem-solving and analytical skills. . Ability to communicate complex technical concepts to both technical and non-technical stakeholders. . Strong ownership mindset and commitment to delivering high-quality solutions. . Preferred Qualifications. Experience with big data ecosystems and real-time analytics platforms. . Exposure to performance benchmarking and capacity planning. . Experience working in Agile/Scrum environments.. Company Location: United States.