AIOps Software Engineer

Quick Facts

• Role: AIOps Software Engineer

• Focus: Analytics and real-time operational platforms for large-scale data systems

Description

You will join a multi-functional team to solve challenging software engineering and operational problems across SDS services. Responsibilities include building applications to answer complex analytical and real-time questions, supporting both analytics and real-time platforms, and driving operational excellence through resilient systems engineering and automation. You will also provide technical leadership, collaborate with MLEs and business partners, and help with infrastructure needs and capacity roadmaps.

Responsibilities

• Support analytics and real-time platforms

• Develop applications for complex analytical and real-time operational questions

• Collaborate with external teams to drive infrastructure development needs

• Design, architect, build, and maintain applications and systems using cloud and AI technologies

• Drive operational excellence via continuous exploration, benchmarking, and resilient operations practices

• Identify opportunities for automation and tool improvements

• Provide hardware architectural guidance, estimate cluster capacity, and create roadmaps

• Provide technical leadership to increase operational maturity across the team

• Work closely with MLEs, other SDS teams, and business partners

• Adjust communication style to meet diverse stakeholder needs

Requirements

• BS or MS in Computer Science preferred; equivalent work experience considered

• 8+ years of experience in Java, Scala, Python, or equivalent

• 8+ years of experience in software engineering, data engineering, or system engineering across the full development lifecycle

• Strong grasp of computer science basics, including data structures and algorithms

• Hands-on experience with Big Data and NoSQL technologies (e.g., Iceberg, S3, Cassandra, Elasticsearch)

• Proven expertise in accelerating software development workflows using AI coding assistants and LLMs like Claude

• Experience with application deployments using Docker and Kubernetes

• Understanding of design and development for large-scale, high-throughput, low-latency applications

• Experience with architectural considerations such as performance, scalability, reusability, and flexibility

• Ability to establish standards, operational excellence, and delivery practices other SDS teams can adopt

• Ability to diagnose and resolve complex technical and operational issues escalated by support and dev teams

• Ability to solve problems collaboratively with business partners

• Proven technical leadership and communication skills

• Strong aptitude to learn new technologies quickly

Benefits

• Opportunity to work on business-critical, large-scale platforms and next-generation customer data solutions

• Technical and operational challenge in a high-demand environment requiring strong time management

• Team culture emphasizes integrity, social skills, and technical craft