AI Principal SW Systems Engineer -AI Infra -Distributed Systems,Microservice, AI Infrastructure,Agentic systems

Overview

AI Principal SW Systems Engineer focused on AI infrastructure for distributed systems, microservices, and agentic AI/automation.

What you'll do

• Define and drive an innovative technical vision across AI networking products and platforms.
• Design and launch capabilities across intelligent networking, distributed systems, real-time data processing, agentic AI, and machine learning.
• Lead the end-to-end software development lifecycle from architecture through operations.
• Design and build scalable, secure, production-ready services and data pipelines for real-time AI platforms.
• Lead technical discussions and participate in design and code reviews while working hands-on.
• Mentor engineers and set technical direction while fostering collaboration and accountability.

What you'll need

• 10 to 18+ years of experience.
• 10+ years across the complete software development lifecycle.
• 10+ years programming experience; preferably Python, Java, Go, or C++.
• 3+ years leading architecture for large-scale distributed systems, preferably on AWS, Azure, or Google Cloud.
• Experience with real-time microservices, stream processing, distributed data platforms, cloud infrastructure, AI or agentic systems, network telemetry, or large-scale analytics.
• Experience processing high-volume, high-velocity data with scalability/availability/latency/reliability requirements.

Nice to have

• Master’s or PhD in Computer Science/Engineering, Electrical Engineering, Machine Learning, or related discipline.
• Experience building generative AI or agentic systems (tool use, planning, memory, retrieval, orchestration, evaluation, deployment).
• Experience with distributed data/processing technologies such as Kafka, Spark, Flink, PySpark, MapReduce.

Details

• Location: Bangalore/Chennai or remote option.