AI Staff SW Systems Engineer

Position :

AI Staff SW Systems Engineer

Skills :

AI, Distributed Systems,Microservice, AI Infrastructure,Agentic systems

Job Responsibilities:

• Serve as a thought leader and forward thinker, helping define and drive an innovative technical vision across our products and platforms. Design and launch strategic capabilities spanning intelligent networking, distributed systems, real-time data processing, agentic AI, and machine learning.
• Lead the end-to-end software development lifecycle, including architecture, design, implementation, testing, deployment, and operations. Lead technical discussions and strategy while participating hands-on in design reviews, code reviews, and implementation.
• Design and build high-performance, production-ready services for next-generation real-time data and AI platforms, including scalable data pipelines, distributed microservices, agentic solutions, and integrations with networking systems.
• Mentor and develop engineers across the team, establish a clear technical direction, and foster a culture of innovation, collaboration, accountability, and engineering excellence.
• Uphold the highest standards of technical rigor and operational excellence. Build highly resilient, secure, observable, and scalable systems, and champion improvements to architecture, engineering processes, system performance, and operational readiness.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent practical experience.
• 7+ years of experience across the complete software development lifecycle, including architecture, design, coding, code reviews, testing, build processes, deployment, and production operations.
• 7+ years of programming experience, with proficiency in at least one general-purpose programming language, preferably Python, Java, Go, or C++.
• 3+ years of experience leading the design and architecture of large-scale distributed systems, preferably on cloud platforms such as AWS, Azure, or Google Cloud.
• Experience in one or more of the following areas: real-time microservices, stream processing, distributed data platforms, cloud infrastructure, AI or agentic systems, network telemetry, or large-scale analytics.
• Experience designing systems that process high-volume, high-velocity data with stringent requirements for scalability, availability, latency, and operational reliability.
• Experience mentoring engineers, serving as a technical lead, or leading an engineering team.
• Demonstrated ability to tackle highly complex, ambiguous, or undefined technical problems and translate them into pragmatic, production-ready solutions.

Preferred Qualifications:

• Master’s or PhD in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or a related discipline, or equivalent practical experience.
• Experience building highly scalable, event-driven microservices and processing large volumes of real-time operational or network data.
• Experience building generative AI or agentic systems, including tool use, planning, memory, retrieval, orchestration, evaluation, and production deployment.
• Experience developing networking, network management, observability, telemetry, cloud infrastructure, or distributed control-plane systems.
• Experience with distributed data and processing technologies such as Kafka, Spark, Flink, PySpark, MapReduce, or comparable technologies.
• Experience working with large-scale, real-world datasets and building reliable production systems that translate data into actionable insights or automated outcomes.