AI Principal Software Systems Engineer – AI Infrastructure, Distributed Systems, Microservices, Agentic Systems

This is a fully remote position, open to applicants in India.

📋 Description

• Establish and propel an innovative technical vision across various products and platforms.

• Create and implement strategic capabilities that encompass intelligent networking, distributed systems, real-time data processing, agentic AI, and machine learning.

• Oversee the complete software development lifecycle, including architecture, design, implementation, testing, deployment, and operations.

• Facilitate technical discussions and strategies while actively participating in design reviews, code assessments, and implementations.

• Develop and construct high-performance, production-ready services tailored for real-time data and AI platforms.

• Construct scalable data pipelines, distributed microservices, agentic solutions, and integrations with networking systems.

• Mentor and nurture engineers, define technical direction, and promote engineering excellence.

• Create resilient, secure, observable, and scalable systems while enhancing architecture, engineering processes, performance, and operational readiness.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.

• Over 10 years of experience throughout the complete software development lifecycle.

• More than 10 years of programming expertise.

• Proficiency in at least one general-purpose programming language, with a preference for Python, Java, Go, or C++.

• At least 3 years of experience leading the design and architecture of large-scale distributed systems.

• Familiarity with real-time microservices, stream processing, distributed data platforms, cloud infrastructure, AI or agentic systems, network telemetry, or large-scale analytics.

• Experience in designing systems that handle high-volume, high-velocity data with strict requirements for scalability, availability, latency, and operational reliability.

• Proven experience in mentoring engineers, acting as a technical lead, or managing an engineering team.

• Capacity to address highly complex, ambiguous, or undefined technical challenges and convert them into practical, production-ready solutions.

• Master’s or PhD in a relevant discipline, or equivalent practical experience (preferred).

• Background in highly scalable, event-driven microservices and real-time operational or network data.

• Experience in developing generative AI or agentic systems, including aspects such as tool use, planning, memory, retrieval, orchestration, evaluation, and production deployment.

• Knowledge of networking, network management, observability, telemetry, cloud infrastructure, or distributed control-plane systems.

• Familiarity with Kafka, Spark, Flink, PySpark, MapReduce, or similar technologies.

• Experience with large-scale, real-world datasets and reliable production systems.

🏝️ Benefits

• Encouragement for individuals from underrepresented groups to apply.

• An inclusive workplace dedicated to fostering an environment where all employees can thrive.

• The opportunity to collaborate with a global leader in networking.

• Exposure to cutting-edge technologies and state-of-the-art software, data, and AI solutions.